Predicting thermal regimes of stream networks across the northeast United States: Natural and anthropogenic influences

EPA Science Inventory

We used STARS (Spatial Tools for the Analysis of River Systems), an ArcGIS geoprocessing toolbox, to create spatial stream networks. We then developed and assessed spatial statistical models for each of these metrics, incorporating spatial autocorrelation based on both distance...

Multi-objective spatial tools to inform maritime spatial planning in the Adriatic Sea.

PubMed

Depellegrin, Daniel; Menegon, Stefano; Farella, Giulio; Ghezzo, Michol; Gissi, Elena; Sarretta, Alessandro; Venier, Chiara; Barbanti, Andrea

2017-12-31

This research presents a set of multi-objective spatial tools for sea planning and environmental management in the Adriatic Sea Basin. The tools address four objectives: 1) assessment of cumulative impacts from anthropogenic sea uses on environmental components of marine areas; 2) analysis of sea use conflicts; 3) 3-D hydrodynamic modelling of nutrient dispersion (nitrogen and phosphorus) from riverine sources in the Adriatic Sea Basin and 4) marine ecosystem services capacity assessment from seabed habitats based on an ES matrix approach. Geospatial modelling results were illustrated, analysed and compared on country level and for three biogeographic subdivisions, Northern-Central-Southern Adriatic Sea. The paper discusses model results for their spatial implications, relevance for sea planning, limitations and concludes with an outlook towards the need for more integrated, multi-functional tools development for sea planning. Copyright © 2017. Published by Elsevier B.V.

[Sociodemographic context of homicide in Mexico City: a spatial analysis].

PubMed

Fuentes Flores, César; Sánchez Salinas, Omar

2015-12-01

Investigate the spatial distribution pattern of the homicide rate and its relation to sociodemographic features in the Benito Juárez, Coyoacán, and Cuauhtémoc districts of Mexico City in 2010. Inferential cross-sectional study that uses spatial analysis methods to study the spatial association of the homicide rate and demographic features. Spatial association was determined through the location quotient, multiple regression analysis, and the use of geographically weighted regression. Homicides show a heterogeneous location pattern with high rates in areas with non-residential land use, low population density, and low marginalization. Spatial analysis tools are powerful instruments for the design of prevention- and recreation-focused public safety policies that aim to reduce mortality from external causes such as homicides.

`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.

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.

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

PubMed Central

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

2013-01-01

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

Guidance on spatial wildland fire analysis: models, tools, and techniques

Treesearch

Richard D. Stratton

2006-01-01

There is an increasing need for spatial wildland fire analysis in support of incident management, fuel treatment planning, wildland-urban assessment, and land management plan development. However, little guidance has been provided to the field in the form of training, support, or research examples. This paper provides guidance to fire managers, planners, specialists,...

Assessing wildfire risks at multiple spatial scales

Treesearch

Justin Fitch

2008-01-01

In continuation of the efforts to advance wildfire science and develop tools for wildland fire managers, a spatial wildfire risk assessment was carried out using Classification and Regression Tree analysis (CART) and Geographic Information Systems (GIS). The analysis was performed at two scales. The small-scale assessment covered the entire state of New Mexico, while...

HydroClimATe: hydrologic and climatic analysis toolkit

USGS Publications Warehouse

Dickinson, Jesse; Hanson, Randall T.; Predmore, Steven K.

2014-01-01

The potential consequences of climate variability and climate change have been identified as major issues for the sustainability and availability of the worldwide water resources. Unlike global climate change, climate variability represents deviations from the long-term state of the climate over periods of a few years to several decades. Currently, rich hydrologic time-series data are available, but the combination of data preparation and statistical methods developed by the U.S. Geological Survey as part of the Groundwater Resources Program is relatively unavailable to hydrologists and engineers who could benefit from estimates of climate variability and its effects on periodic recharge and water-resource availability. This report documents HydroClimATe, a computer program for assessing the relations between variable climatic and hydrologic time-series data. HydroClimATe was developed for a Windows operating system. The software includes statistical tools for (1) time-series preprocessing, (2) spectral analysis, (3) spatial and temporal analysis, (4) correlation analysis, and (5) projections. The time-series preprocessing tools include spline fitting, standardization using a normal or gamma distribution, and transformation by a cumulative departure. The spectral analysis tools include discrete Fourier transform, maximum entropy method, and singular spectrum analysis. The spatial and temporal analysis tool is empirical orthogonal function analysis. The correlation analysis tools are linear regression and lag correlation. The projection tools include autoregressive time-series modeling and generation of many realizations. These tools are demonstrated in four examples that use stream-flow discharge data, groundwater-level records, gridded time series of precipitation data, and the Multivariate ENSO Index.

A Cognitive Component Analysis Approach for Developing Game-Based Spatial Learning Tools

ERIC Educational Resources Information Center

Hung, Pi-Hsia; Hwang, Gwo-Jen; Lee, Yueh-Hsun; Su, I-Hsiang

2012-01-01

Spatial ability has been recognized as one of the most important factors affecting the mathematical performance of students. Previous studies on spatial learning have mainly focused on developing strategies to shorten the problem-solving time of learners for very specific learning tasks. Such an approach usually has limited effects on improving…

Spatially resolved chemical analysis of cicada wings using laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS).

PubMed

Román, Jessica K; Walsh, Callee M; Oh, Junho; Dana, Catherine E; Hong, Sungmin; Jo, Kyoo D; Alleyne, Marianne; Miljkovic, Nenad; Cropek, Donald M

2018-03-01

Laser-ablation electrospray ionization (LAESI) imaging mass spectrometry (IMS) is an emerging bioanalytical tool for direct imaging and analysis of biological tissues. Performing ionization in an ambient environment, this technique requires little sample preparation and no additional matrix, and can be performed on natural, uneven surfaces. When combined with optical microscopy, the investigation of biological samples by LAESI allows for spatially resolved compositional analysis. We demonstrate here the applicability of LAESI-IMS for the chemical analysis of thin, desiccated biological samples, specifically Neotibicen pruinosus cicada wings. Positive-ion LAESI-IMS accurate ion-map data was acquired from several wing cells and superimposed onto optical images allowing for compositional comparisons across areas of the wing. Various putative chemical identifications were made indicating the presence of hydrocarbons, lipids/esters, amines/amides, and sulfonated/phosphorylated compounds. With the spatial resolution capability, surprising chemical distribution patterns were observed across the cicada wing, which may assist in correlating trends in surface properties with chemical distribution. Observed ions were either (1) equally dispersed across the wing, (2) more concentrated closer to the body of the insect (proximal end), or (3) more concentrated toward the tip of the wing (distal end). These findings demonstrate LAESI-IMS as a tool for the acquisition of spatially resolved chemical information from fragile, dried insect wings. This LAESI-IMS technique has important implications for the study of functional biomaterials, where understanding the correlation between chemical composition, physical structure, and biological function is critical. Graphical abstract Positive-ion laser-ablation electrospray ionization mass spectrometry coupled with optical imaging provides a powerful tool for the spatially resolved chemical analysis of cicada wings.

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.

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.

Web-based access, aggregation, and visualization of future climate projections with emphasis on agricultural assessments

NASA Astrophysics Data System (ADS)

Villoria, Nelson B.; Elliott, Joshua; Müller, Christoph; Shin, Jaewoo; Zhao, Lan; Song, Carol

2018-01-01

Access to climate and spatial datasets by non-specialists is restricted by technical barriers involving hardware, software and data formats. We discuss an open-source online tool that facilitates downloading the climate data from the global circulation models used by the Inter-Sectoral Impacts Model Intercomparison Project. The tool also offers temporal and spatial aggregation capabilities for incorporating future climate scenarios in applications where spatial aggregation is important. We hope that streamlined access to these data facilitates analysis of climate related issues while considering the uncertainties derived from future climate projections and temporal aggregation choices.

Environmental Tools and Radiological Assessment

EPA Science Inventory

This presentation details two tools (SADA and FRAMES) available for use in environmental assessments of chemicals that can also be used for radiological assessments of the environment. Spatial Analysis and Decision Assistance (SADA) is a Windows freeware program that incorporate...

Creating a spatially-explicit index: a method for assessing the global wildfire-water risk

NASA Astrophysics Data System (ADS)

Robinne, François-Nicolas; Parisien, Marc-André; Flannigan, Mike; Miller, Carol; Bladon, Kevin D.

2017-04-01

The wildfire-water risk (WWR) has been defined as the potential for wildfires to adversely affect water resources that are important for downstream ecosystems and human water needs for adequate water quantity and quality, therefore compromising the security of their water supply. While tools and methods are numerous for watershed-scale risk analysis, the development of a toolbox for the large-scale evaluation of the wildfire risk to water security has only started recently. In order to provide managers and policy-makers with an adequate tool, we implemented a method for the spatial analysis of the global WWR based on the Driving forces-Pressures-States-Impacts-Responses (DPSIR) framework. This framework relies on the cause-and-effect relationships existing between the five categories of the DPSIR chain. As this approach heavily relies on data, we gathered an extensive set of spatial indicators relevant to fire-induced hydrological hazards and water consumption patterns by human and natural communities. When appropriate, we applied a hydrological routing function to our indicators in order to simulate downstream accumulation of potentially harmful material. Each indicator was then assigned a DPSIR category. We collapsed the information in each category using a principal component analysis in order to extract the most relevant pixel-based information provided by each spatial indicator. Finally, we compiled our five categories using an additive indexation process to produce a spatially-explicit index of the WWR. A thorough sensitivity analysis has been performed in order to understand the relationship between the final risk values and the spatial pattern of each category used during the indexation. For comparison purposes, we aggregated index scores by global hydrological regions, or hydrobelts, to get a sense of regional DPSIR specificities. This rather simple method does not necessitate the use of complex physical models and provides a scalable and efficient tool for the analysis of global water security issues.

Geographic information systems: introduction.

PubMed

Calistri, Paolo; Conte, Annamaria; Freier, Jerome E; Ward, Michael P

2007-01-01

The recent exponential growth of the science and technology of geographic information systems (GIS) has made a tremendous contribution to epidemiological analysis and has led to the development of new powerful tools for the surveillance of animal diseases. GIS, spatial analysis and remote sensing provide valuable methods to collect and manage information for epidemiological surveys. Spatial patterns and trends of disease can be correlated with climatic and environmental information, thus contributing to a better understanding of the links between disease processes and explanatory spatial variables. Until recently, these tools were underexploited in the field of veterinary public health, due to the prohibitive cost of hardware and the complexity of GIS software that required a high level of expertise. The revolutionary developments in computer performance of the last decade have not only reduced the costs of equipment but have made available easy-to-use Web-based software which in turn have meant that GIS are more widely accessible by veterinary services at all levels. At the same time, the increased awareness of the possibilities offered by these tools has created new opportunities for decision-makers to enhance their planning, analysis and monitoring capabilities. These technologies offer a new way of sharing and accessing spatial and non-spatial data across groups and institutions. The series of papers included in this compilation aim to: - define the state of the art in the use of GIS in veterinary activities - identify priority needs in the development of new GIS tools at the international level for the surveillance of animal diseases and zoonoses - define practical proposals for their implementation. The topics addressed are presented in the following order in this book: - importance of GIS for the monitoring of animal diseases and zoonoses - GIS application in surveillance activities - spatial analysis in veterinary epidemiology - data collection and remote sensing applications - Web - GIS as a tool for data and knowledge sharing. All 43 manuscripts selected for this book have been peer-reviewed. These contributions were originally commissioned for the First international conference on the use of GIS in veterinary activities organised by the Istituto Zooprofilattico Sperimentale dell'Abruzzo e del Molise 'G. Caporale', Teramo, Italy, and the World Organisation for Animal Health (OIE: Office International des Epizooties) that was held in Silvi Marina, Italy, from 8 to 11 October 2006. The editors would like to thank all authors for their valuable contributions.

Dynamic Hurricane Data Analysis Tool

NASA Technical Reports Server (NTRS)

Knosp, Brian W.; Li, Peggy; Vu, Quoc A.

2009-01-01

A dynamic hurricane data analysis tool allows users of the JPL Tropical Cyclone Information System (TCIS) to analyze data over a Web medium. The TCIS software is described in the previous article, Tropical Cyclone Information System (TCIS) (NPO-45748). This tool interfaces with the TCIS database to pull in data from several different atmospheric and oceanic data sets, both observed by instruments. Users can use this information to generate histograms, maps, and profile plots for specific storms. The tool also displays statistical values for the user-selected parameter for the mean, standard deviation, median, minimum, and maximum values. There is little wait time, allowing for fast data plots over date and spatial ranges. Users may also zoom-in for a closer look at a particular spatial range. This is version 1 of the software. Researchers will use the data and tools on the TCIS to understand hurricane processes, improve hurricane forecast models and identify what types of measurements the next generation of instruments will need to collect.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

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

Developing Automated Spectral Analysis Tools for Interstellar Features Extractionto Support Construction of the 3D ISM Map

NASA Astrophysics Data System (ADS)

Puspitarini, L.; Lallement, R.; Monreal-Ibero, A.; Chen, H.-C.; Malasan, H. L.; Aprilia; Arifyanto, M. I.; Irfan, M.

2018-04-01

One of the ways to obtain a detailed 3D ISM map is by gathering interstellar (IS) absorption data toward widely distributed background target stars at known distances (line-of-sight/LOS data). The radial and angular evolution of the LOS measurements allow the inference of the ISM spatial distribution. For a better spatial resolution, one needs a large number of the LOS data. It requires building fast tools to measure IS absorption. One of the tools is a global analysis that fit two different diffuse interstellar bands (DIBs) simultaneously. We derived the equivalent width (EW) ratio of the two DIBs recorded in each spectrum of target stars. The ratio variability can be used to study IS environmental conditions or to detect DIB family.

AgBufferBuilder: A geographic information system (GIS) tool for precision design and performance assessment of filter strips

Treesearch

M. G. Dosskey; S. Neelakantan; T. G. Mueller; T. Kellerman; M. J. Helmers; E. Rienzi

2015-01-01

Spatially nonuniform runoif reduces the water qua1iry perfortnance of constant- width filter strips. A geographic inlormation system (Gls)-based tool was developed and tested that ernploys terrain analysis to account lor spatially nonuniform runoffand produce more ellbctive filter strip designs.The computer program,AgBufTerBuilder, runs with ATcGIS versions 10.0 and 10...

A high-performance spatial database based approach for pathology imaging algorithm evaluation

PubMed Central

Wang, Fusheng; Kong, Jun; Gao, Jingjing; Cooper, Lee A.D.; Kurc, Tahsin; Zhou, Zhengwen; Adler, David; Vergara-Niedermayr, Cristobal; Katigbak, Bryan; Brat, Daniel J.; Saltz, Joel H.

2013-01-01

Background: Algorithm evaluation provides a means to characterize variability across image analysis algorithms, validate algorithms by comparison with human annotations, combine results from multiple algorithms for performance improvement, and facilitate algorithm sensitivity studies. The sizes of images and image analysis results in pathology image analysis pose significant challenges in algorithm evaluation. We present an efficient parallel spatial database approach to model, normalize, manage, and query large volumes of analytical image result data. This provides an efficient platform for algorithm evaluation. Our experiments with a set of brain tumor images demonstrate the application, scalability, and effectiveness of the platform. Context: The paper describes an approach and platform for evaluation of pathology image analysis algorithms. The platform facilitates algorithm evaluation through a high-performance database built on the Pathology Analytic Imaging Standards (PAIS) data model. Aims: (1) Develop a framework to support algorithm evaluation by modeling and managing analytical results and human annotations from pathology images; (2) Create a robust data normalization tool for converting, validating, and fixing spatial data from algorithm or human annotations; (3) Develop a set of queries to support data sampling and result comparisons; (4) Achieve high performance computation capacity via a parallel data management infrastructure, parallel data loading and spatial indexing optimizations in this infrastructure. Materials and Methods: We have considered two scenarios for algorithm evaluation: (1) algorithm comparison where multiple result sets from different methods are compared and consolidated; and (2) algorithm validation where algorithm results are compared with human annotations. We have developed a spatial normalization toolkit to validate and normalize spatial boundaries produced by image analysis algorithms or human annotations. The validated data were formatted based on the PAIS data model and loaded into a spatial database. To support efficient data loading, we have implemented a parallel data loading tool that takes advantage of multi-core CPUs to accelerate data injection. The spatial database manages both geometric shapes and image features or classifications, and enables spatial sampling, result comparison, and result aggregation through expressive structured query language (SQL) queries with spatial extensions. To provide scalable and efficient query support, we have employed a shared nothing parallel database architecture, which distributes data homogenously across multiple database partitions to take advantage of parallel computation power and implements spatial indexing to achieve high I/O throughput. Results: Our work proposes a high performance, parallel spatial database platform for algorithm validation and comparison. This platform was evaluated by storing, managing, and comparing analysis results from a set of brain tumor whole slide images. The tools we develop are open source and available to download. Conclusions: Pathology image algorithm validation and comparison are essential to iterative algorithm development and refinement. One critical component is the support for queries involving spatial predicates and comparisons. In our work, we develop an efficient data model and parallel database approach to model, normalize, manage and query large volumes of analytical image result data. Our experiments demonstrate that the data partitioning strategy and the grid-based indexing result in good data distribution across database nodes and reduce I/O overhead in spatial join queries through parallel retrieval of relevant data and quick subsetting of datasets. The set of tools in the framework provide a full pipeline to normalize, load, manage and query analytical results for algorithm evaluation. PMID:23599905

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

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

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

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

Delineating resource sheds in aquatic ecosystems (presentation)

EPA Science Inventory

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

In-situ chemical imager

NASA Technical Reports Server (NTRS)

Kossakovski, D. A.; Bearman, G. H.; Kirschvink, J. L.

2000-01-01

A variety of in-situ planetary exploration tasks such as particulate analysis or life detection require a tool with a capability for combined imaging and chemical analysis with sub-micron spatial resolution.

Multiscale recurrence analysis of spatio-temporal data

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Multiscale recurrence analysis of spatio-temporal data.

PubMed

Riedl, M; Marwan, N; Kurths, J

2015-12-01

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

Ground subsidence information as a valuable layer in GIS analysis

NASA Astrophysics Data System (ADS)

Murdzek, Radosław; Malik, Hubert; Leśniak, Andrzej

2018-04-01

Among the technologies used to improve functioning of local governments the geographic information systems (GIS) are widely used. GIS tools allow to simultaneously integrate spatial data resources, analyse them, process and use them to make strategic decisions. Nowadays GIS analysis is widely used in spatial planning or environmental protection. In these applications a number of spatial information are utilized, but rarely it is an information about environmental hazards. This paper includes information about ground subsidence that occurred in USCB mining area into GIS analysis. Monitoring of this phenomenon can be carried out using the radar differential interferometry (DInSAR) method.

Traverse Planning with Temporal-Spatial Constraints

NASA Technical Reports Server (NTRS)

Bresina, John L.; Morris, Paul H.; Deans, Mathew C.; Cohen, Tamar E.; Lees, David S.

2017-01-01

We present an approach to planning rover traverses in a domain that includes temporal-spatial constraints. We are using the NASA Resource Prospector mission as a reference mission in our research. The objective of this mission is to explore permanently shadowed regions at a Lunar pole. Most of the time the rover is required to avoid being in shadow. This requirement depends on where the rover is located and when it is at that location. Such a temporal-spatial constraint makes traverse planning more challenging for both humans and machines. We present a mixed-initiative traverse planner which addresses this challenge. This traverse planner is part of the Exploration Ground Data Systems (xGDS), which we have enhanced with new visualization features, new analysis tools, and new automation for path planning, in order to be applicable to the Re-source Prospector mission. The key concept that is the basis of the analysis tools and that supports the automated path planning is reachability in this dynamic environment due to the temporal-spatial constraints.

Spatial Analysis of China Province-level Perinatal Mortality

PubMed Central

XIANG, Kun; SONG, Deyong

2016-01-01

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

Mapping and spatiotemporal analysis tool for hydrological data: Spellmap

USDA-ARS?s Scientific Manuscript database

Lack of data management and analyses tools is one of the major limitations to effectively evaluate and use large datasets of high-resolution atmospheric, surface, and subsurface observations. High spatial and temporal resolution datasets better represent the spatiotemporal variability of hydrologica...

The Stratification Analysis of Sediment Data for Lake Michigan

EPA Science Inventory

This research paper describes the development of spatial statistical tools that are applied to investigate the spatial trends of sediment data sets for nutrients and carbon in Lake Michigan. All of the sediment data utilized in the present study was collected over a two year per...

Research on the spatial analysis method of seismic hazard for island

NASA Astrophysics Data System (ADS)

Jia, Jing; Jiang, Jitong; Zheng, Qiuhong; Gao, Huiying

2017-05-01

Seismic hazard analysis(SHA) is a key component of earthquake disaster prevention field for island engineering, whose result could provide parameters for seismic design microscopically and also is the requisite work for the island conservation planning’s earthquake and comprehensive disaster prevention planning macroscopically, in the exploitation and construction process of both inhabited and uninhabited islands. The existing seismic hazard analysis methods are compared in their application, and their application and limitation for island is analysed. Then a specialized spatial analysis method of seismic hazard for island (SAMSHI) is given to support the further related work of earthquake disaster prevention planning, based on spatial analysis tools in GIS and fuzzy comprehensive evaluation model. The basic spatial database of SAMSHI includes faults data, historical earthquake record data, geological data and Bouguer gravity anomalies data, which are the data sources for the 11 indices of the fuzzy comprehensive evaluation model, and these indices are calculated by the spatial analysis model constructed in ArcGIS’s Model Builder platform.

Tackling the 2nd V: Big Data, Variety and the Need for Representation Consistency

NASA Astrophysics Data System (ADS)

Clune, T.; Kuo, K. S.

2016-12-01

While Big Data technologies are transforming our ability to analyze ever larger volumes of Earth science data, practical constraints continue to limit our ability to compare data across datasets from different sources in an efficient and robust manner. Within a single data collection, invariants such as file format, grid type, and spatial resolution greatly simplify many types of analysis (often implicitly). However, when analysis combines data across multiple data collections, researchers are generally required to implement data transformations (i.e., "data preparation") to provide appropriate invariants. These transformation include changing of file formats, ingesting into a database, and/or regridding to a common spatial representation, and they can either be performed once, statically, or each time the data is accessed. At the very least, this process is inefficient from the perspective of the community as each team selects its own representation and privately implements the appropriate transformations. No doubt there are disadvantages to any "universal" representation, but we posit that major benefits would be obtained if a suitably flexible spatial representation could be standardized along with tools for transforming to/from that representation. We regard this as part of the historic trend in data publishing. Early datasets used ad hoc formats and lacked metadata. As better tools evolved, published data began to use standardized formats (e.g., HDF and netCDF) with attached metadata. We propose that the modern need to perform analysis across data sets should drive a new generation of tools that support a standardized spatial representation. More specifically, we propose the hierarchical triangular mesh (HTM) as a suitable "generic" resolution that permits standard transformations to/from native representations in use today, as well as tools to convert/regrid existing datasets onto that representation.

Spatial decision support system to evaluate crop residue energy potential by anaerobic digestion.

PubMed

Escalante, Humberto; Castro, Liliana; Gauthier-Maradei, Paola; Rodríguez De La Vega, Reynel

2016-11-01

Implementing anaerobic digestion (AD) in energy production from crop residues requires development of decision tools to assess its feasibility and sustainability. A spatial decision support system (SDSS) was constructed to assist decision makers to select appropriate feedstock according to biomethanation potential, identify the most suitable location for biogas facilities, determine optimum plant capacity and supply chain, and evaluate associated risks and costs. SDSS involves a spatially explicit analysis, fuzzy multi-criteria analysis, and statistical and optimization models. The tool was validated on seven crop residues located in Santander, Colombia. For example, fique bagasse generates about 0.21millionm(3)CH4year(-1) (0.329m(3)CH4kg(-1) volatile solids) with a minimum profitable plant of about 2000tonyear(-1) and an internal rate of return of 10.5%. SDSS can be applied to evaluate other biomass resources, availability periods, and co-digestion potential. Copyright © 2016. Published by Elsevier Ltd.

Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis

NASA Astrophysics Data System (ADS)

Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang

Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.

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

ERIC Educational Resources Information Center

González Canché, Manuel S.

2018-01-01

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

Mid-infrared thermal imaging for an effective mapping of surface materials and sub-surface detachments in mural paintings: integration of thermography and thermal quasi-reflectography

NASA Astrophysics Data System (ADS)

Daffara, C.; Parisotto, S.; Mariotti, P. I.

2015-06-01

Cultural Heritage is discovering how precious is thermal analysis as a tool to improve the restoration, thanks to its ability to inspect hidden details. In this work a novel dual mode imaging approach, based on the integration of thermography and thermal quasi-reflectography (TQR) in the mid-IR is demonstrated for an effective mapping of surface materials and of sub-surface detachments in mural painting. The tool was validated through a unique application: the "Monocromo" by Leonardo da Vinci in Italy. The dual mode acquisition provided two spatially aligned dataset: the TQR image and the thermal sequence. Main steps of the workflow included: 1) TQR analysis to map surface features and 2) to estimate the emissivity; 3) projection of the TQR frame on reference orthophoto and TQR mosaicking; 4) thermography analysis to map detachments; 5) use TQR to solve spatial referencing and mosaicking for the thermal-processed frames. Referencing of thermal images in the visible is a difficult aspect of the thermography technique that the dual mode approach allows to solve in effective way. We finally obtained the TQR and the thermal maps spatially referenced to the mural painting, thus providing the restorer a valuable tool for the restoration of the detachments.

An online spatial database of Australian Indigenous Biocultural Knowledge for contemporary natural and cultural resource management.

PubMed

Pert, Petina L; Ens, Emilie J; Locke, John; Clarke, Philip A; Packer, Joanne M; Turpin, Gerry

2015-11-15

With growing international calls for the enhanced involvement of Indigenous peoples and their biocultural knowledge in managing conservation and the sustainable use of physical environment, it is timely to review the available literature and develop cross-cultural approaches to the management of biocultural resources. Online spatial databases are becoming common tools for educating land managers about Indigenous Biocultural Knowledge (IBK), specifically to raise a broad awareness of issues, identify knowledge gaps and opportunities, and to promote collaboration. Here we describe a novel approach to the application of internet and spatial analysis tools that provide an overview of publically available documented Australian IBK (AIBK) and outline the processes used to develop the online resource. By funding an AIBK working group, the Australian Centre for Ecological Analysis and Synthesis (ACEAS) provided a unique opportunity to bring together cross-cultural, cross-disciplinary and trans-organizational contributors who developed these resources. Without such an intentionally collaborative process, this unique tool would not have been developed. The tool developed through this process is derived from a spatial and temporal literature review, case studies and a compilation of methods, as well as other relevant AIBK papers. The online resource illustrates the depth and breadth of documented IBK and identifies opportunities for further work, partnerships and investment for the benefit of not only Indigenous Australians, but all Australians. The database currently includes links to over 1500 publically available IBK documents, of which 568 are geo-referenced and were mapped. It is anticipated that as awareness of the online resource grows, more documents will be provided through the website to build the database. It is envisaged that this will become a well-used tool, integral to future natural and cultural resource management and maintenance. Copyright © 2015. Published by Elsevier B.V.

New tools for linking human and earth system models: The Toolbox for Human-Earth System Interaction & Scaling (THESIS)

NASA Astrophysics Data System (ADS)

O'Neill, B. C.; Kauffman, B.; Lawrence, P.

2016-12-01

Integrated analysis of questions regarding land, water, and energy resources often requires integration of models of different types. One type of integration is between human and earth system models, since both societal and physical processes influence these resources. For example, human processes such as changes in population, economic conditions, and policies govern the demand for land, water and energy, while the interactions of these resources with physical systems determine their availability and environmental consequences. We have begun to develop and use a toolkit for linking human and earth system models called the Toolbox for Human-Earth System Integration and Scaling (THESIS). THESIS consists of models and software tools to translate, scale, and synthesize information from and between human system models and earth system models (ESMs), with initial application to linking the NCAR integrated assessment model, iPETS, with the NCAR earth system model, CESM. Initial development is focused on urban areas and agriculture, sectors that are both explicitly represented in both CESM and iPETS. Tools are being made available to the community as they are completed (see https://www2.cgd.ucar.edu/sections/tss/iam/THESIS_tools). We discuss four general types of functions that THESIS tools serve (Spatial Distribution, Spatial Properties, Consistency, and Outcome Evaluation). Tools are designed to be modular and can be combined in order to carry out more complex analyses. We illustrate their application to both the exposure of population to climate extremes and to the evaluation of climate impacts on the agriculture sector. For example, projecting exposure to climate extremes involves use of THESIS tools for spatial population, spatial urban land cover, the characteristics of both, and a tool to bring urban climate information together with spatial population information. Development of THESIS tools is continuing and open to the research community.

Evaluating Hyperspectral Imaging of Wetland Vegetation as a Tool for Detecting Estuarine Nutrient Enrichment

DTIC Science & Technology

2008-05-01

the vegetation’s uptake of water column nutrients produces a spectral response; and 3) the spectral and spatial resolutions ...analysis. This allowed us to evaluate these assumptions at the landscape level, by using the high spectral and spatial resolution of the hyperspectral... spatial resolution (2.5 m pixels) HyMap hyperspectral imagery of the entire wetland. After using a hand-held spectrometer to characterize

A Navigation Analysis Tool (NAT) to assess spatial behavior in open-field and structured mazes.

PubMed

Jarlier, Frédéric; Arleo, Angelo; Petit, Géraldine H; Lefort, Julie M; Fouquet, Céline; Burguière, Eric; Rondi-Reig, Laure

2013-05-15

Spatial navigation calls upon mnemonic capabilities (e.g. remembering the location of a rewarding site) as well as adaptive motor control (e.g. fine tuning of the trajectory according to the ongoing sensory context). To study this complex process by means of behavioral measurements it is necessary to quantify a large set of meaningful parameters on multiple time scales (from milliseconds to several minutes), and to compare them across different paradigms. Moreover, the issue of automating the behavioral analysis is critical to cope with the consequent computational load and the sophistication of the measurements. We developed a general purpose Navigation Analysis Tool (NAT) that provides an integrated architecture consisting of a data management system (implemented in MySQL), a core analysis toolbox (in MATLAB), and a graphical user interface (in JAVA). Its extensive characterization of trajectories over time, from exploratory behavior to goal-oriented navigation with decision points using a wide range of parameters, makes NAT a powerful analysis tool. In particular, NAT supplies a new set of specific measurements assessing performances in multiple intersection mazes and allowing navigation strategies to be discriminated (e.g. in the starmaze). Its user interface enables easy use while its modular organization provides many opportunities of extension and customization. Importantly, the portability of NAT to any type of maze and environment extends its exploitation far beyond the field of spatial navigation. Copyright © 2013 Elsevier B.V. All rights reserved.

The analysis of inland water transport on technically developed Polish section of the E70 waterway using GIS tools in the years 2005-2014

NASA Astrophysics Data System (ADS)

Rabant, Hubert; Szatten, Dawid; Nadolny, Grzegorz

2017-11-01

The article presents the characteristics of changes in the spatial extent of transport on the hydrotechnically developed section of the E70 waterway in Poland using methods and tools of geographic information systems (GIS). The results of the analyzes show the conditions for vessel traffic, their type and volatility in the years 2005-2014. The methods made it possible to analyze the spatial determinants of navigation. The obtained results were referred to the current state and prospects for development of Polish waterways and indicated that the applied tools have a great application role in the research on their logistics and development.

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

PubMed

Bui, Thanh Quang; Pham, Hai Minh

2016-01-01

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

Spatial modeling of potential woody biomass flow

Treesearch

Woodam Chung; Nathaniel Anderson

2012-01-01

The flow of woody biomass to end users is determined by economic factors, especially the amount available across a landscape and delivery costs of bioenergy facilities. The objective of this study develop methodology to quantify landscape-level stocks and potential biomass flows using the currently available spatial database road network analysis tool. We applied this...

Application of GIS Rapid Mapping Technology in Disaster Monitoring

NASA Astrophysics Data System (ADS)

Wang, Z.; Tu, J.; Liu, G.; Zhao, Q.

2018-04-01

With the rapid development of GIS and RS technology, especially in recent years, GIS technology and its software functions have been increasingly mature and enhanced. And with the rapid development of mathematical statistical tools for spatial modeling and simulation, has promoted the widespread application and popularization of quantization in the field of geology. Based on the investigation of field disaster and the construction of spatial database, this paper uses remote sensing image, DEM and GIS technology to obtain the data information of disaster vulnerability analysis, and makes use of the information model to carry out disaster risk assessment mapping.Using ArcGIS software and its spatial data modeling method, the basic data information of the disaster risk mapping process was acquired and processed, and the spatial data simulation tool was used to map the disaster rapidly.

A Quantitative Three-Dimensional Image Analysis Tool for Maximal Acquisition of Spatial Heterogeneity Data.

PubMed

Allenby, Mark C; Misener, Ruth; Panoskaltsis, Nicki; Mantalaris, Athanasios

2017-02-01

Three-dimensional (3D) imaging techniques provide spatial insight into environmental and cellular interactions and are implemented in various fields, including tissue engineering, but have been restricted by limited quantification tools that misrepresent or underutilize the cellular phenomena captured. This study develops image postprocessing algorithms pairing complex Euclidean metrics with Monte Carlo simulations to quantitatively assess cell and microenvironment spatial distributions while utilizing, for the first time, the entire 3D image captured. Although current methods only analyze a central fraction of presented confocal microscopy images, the proposed algorithms can utilize 210% more cells to calculate 3D spatial distributions that can span a 23-fold longer distance. These algorithms seek to leverage the high sample cost of 3D tissue imaging techniques by extracting maximal quantitative data throughout the captured image.

GuidosToolbox: universal digital image object analysis

Treesearch

Peter Vogt; Kurt Riitters

2017-01-01

The increased availability of mapped environmental data calls for better tools to analyze the spatial characteristics and information contained in those maps. Publicly available, userfriendly and universal tools are needed to foster the interdisciplinary development and application of methodologies for the extraction of image object information properties contained in...

Construction of a Distributed-network Digital Watershed Management System with B/S Techniques

NASA Astrophysics Data System (ADS)

Zhang, W. C.; Liu, Y. M.; Fang, J.

2017-07-01

Integrated watershed assessment tools for supporting land management and hydrologic research are becoming established tools in both basic and applied research. The core of these tools are mainly spatially distributed hydrologic models as they can provide a mechanism for investigating interactions among climate, topography, vegetation, and soil. However, the extensive data requirements and the difficult task of building input parameter files for driving these distributed models, have long been an obstacle to the timely and cost-effective use of such complex models by watershed managers and policy-makers. Recently, a web based geographic information system (GIS) tool to facilitate this process has been developed for a large watersheds of Jinghe and Weihe catchments located in the loess plateau of the Huanghe River basin in north-western China. A web-based GIS provides the framework within which spatially distributed data are collected and used to prepare model input files of these two watersheds and evaluate model results as well as to provide the various clients for watershed information inquiring, visualizing and assessment analysis. This Web-based Automated Geospatial Watershed Assessment GIS (WAGWA-GIS) tool uses widely available standardized spatial datasets that can be obtained via the internet oracle databank designed with association of Map Guide platform to develop input parameter files for online simulation at different spatial and temporal scales with Xing’anjiang and TOPMODEL that integrated with web-based digital watershed. WAGWA-GIS automates the process of transforming both digital data including remote sensing data, DEM, Land use/cover, soil digital maps and meteorological and hydrological station geo-location digital maps and text files containing meteorological and hydrological data obtained from stations of the watershed into hydrological models for online simulation and geo-spatial analysis and provides a visualization tool to help the user interpret results. The utility of WAGWA-GIS in jointing hydrologic and ecological investigations has been demonstrated on such diverse landscapes as Jinhe and Weihe watersheds, and will be extended to be utilized in the other watersheds in China step by step in coming years

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

NASA Technical Reports Server (NTRS)

Hale, Joseph P., II

1994-01-01

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

Development of efficient and cost-effective distributed hydrological modeling tool MWEasyDHM based on open-source MapWindow GIS

NASA Astrophysics Data System (ADS)

Lei, Xiaohui; Wang, Yuhui; Liao, Weihong; Jiang, Yunzhong; Tian, Yu; Wang, Hao

2011-09-01

Many regions are still threatened with frequent floods and water resource shortage problems in China. Consequently, the task of reproducing and predicting the hydrological process in watersheds is hard and unavoidable for reducing the risks of damage and loss. Thus, it is necessary to develop an efficient and cost-effective hydrological tool in China as many areas should be modeled. Currently, developed hydrological tools such as Mike SHE and ArcSWAT (soil and water assessment tool based on ArcGIS) show significant power in improving the precision of hydrological modeling in China by considering spatial variability both in land cover and in soil type. However, adopting developed commercial tools in such a large developing country comes at a high cost. Commercial modeling tools usually contain large numbers of formulas, complicated data formats, and many preprocessing or postprocessing steps that may make it difficult for the user to carry out simulation, thus lowering the efficiency of the modeling process. Besides, commercial hydrological models usually cannot be modified or improved to be suitable for some special hydrological conditions in China. Some other hydrological models are open source, but integrated into commercial GIS systems. Therefore, by integrating hydrological simulation code EasyDHM, a hydrological simulation tool named MWEasyDHM was developed based on open-source MapWindow GIS, the purpose of which is to establish the first open-source GIS-based distributed hydrological model tool in China by integrating modules of preprocessing, model computation, parameter estimation, result display, and analysis. MWEasyDHM provides users with a friendly manipulating MapWindow GIS interface, selectable multifunctional hydrological processing modules, and, more importantly, an efficient and cost-effective hydrological simulation tool. The general construction of MWEasyDHM consists of four major parts: (1) a general GIS module for hydrological analysis, (2) a preprocessing module for modeling inputs, (3) a model calibration module, and (4) a postprocessing module. The general GIS module for hydrological analysis is developed on the basis of totally open-source GIS software, MapWindow, which contains basic GIS functions. The preprocessing module is made up of three submodules including a DEM-based submodule for hydrological analysis, a submodule for default parameter calculation, and a submodule for the spatial interpolation of meteorological data. The calibration module contains parallel computation, real-time computation, and visualization. The postprocessing module includes model calibration and model results spatial visualization using tabular form and spatial grids. MWEasyDHM makes it possible for efficient modeling and calibration of EasyDHM, and promises further development of cost-effective applications in various watersheds.

Part 3 Specialized aspects of GIS and spatial analysis . Garage band science and dynamic spatial models

NASA Astrophysics Data System (ADS)

Box, Paul W.

GIS and spatial analysis is suited mainly for static pictures of the landscape, but many of the processes that need exploring are dynamic in nature. Dynamic processes can be complex when put in a spatial context; our ability to study such processes will probably come with advances in understanding complex systems in general. Cellular automata and agent-based models are two prime candidates for exploring complex spatial systems, but are difficult to implement. Innovative tools that help build complex simulations will create larger user communities, who will probably find novel solutions for understanding complexity. A significant source for such innovations is likely to be from the collective efforts of hobbyists and part-time programmers, who have been dubbed ``garage-band scientists'' in the popular press.

Development of spatial data guidelines and standards: spatial data set documentation to support hydrologic analysis in the U.S. Geological Survey

USGS Publications Warehouse

Fulton, James L.

1992-01-01

Spatial data analysis has become an integral component in many surface and sub-surface hydrologic investigations within the U.S. Geological Survey (USGS). Currently, one of the largest costs in applying spatial data analysis is the cost of developing the needed spatial data. Therefore, guidelines and standards are required for the development of spatial data in order to allow for data sharing and reuse; this eliminates costly redevelopment. In order to attain this goal, the USGS is expanding efforts to identify guidelines and standards for the development of spatial data for hydrologic analysis. Because of the variety of project and database needs, the USGS has concentrated on developing standards for documenting spatial sets to aid in the assessment of data set quality and compatibility of different data sets. An interim data set documentation standard (1990) has been developed that provides a mechanism for associating a wide variety of information with a data set, including data about source material, data automation and editing procedures used, projection parameters, data statistics, descriptions of features and feature attributes, information on organizational contacts lists of operations performed on the data, and free-form comments and notes about the data, made at various times in the evolution of the data set. The interim data set documentation standard has been automated using a commercial geographic information system (GIS) and data set documentation software developed by the USGS. Where possible, USGS developed software is used to enter data into the data set documentation file automatically. The GIS software closely associates a data set with its data set documentation file; the documentation file is retained with the data set whenever it is modified, copied, or transferred to another computer system. The Water Resources Division of the USGS is continuing to develop spatial data and data processing standards, with emphasis on standards needed to support hydrologic analysis, hydrologic data processing, and publication of hydrologic thermatic maps. There is a need for the GIS vendor community to develop data set documentation tools similar to those developed by the USGS, or to incorporate USGS developed tools in their software.

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

PubMed Central

2011-01-01

The complex epidemiology of vector-borne diseases creates significant challenges in the design and delivery of prevention and control strategies, especially in light of rapid social and environmental changes. Spatial models for predicting disease risk based on environmental factors such as climate and landscape have been developed for a number of important vector-borne diseases. The resulting risk maps have proven value for highlighting areas for targeting public health programs. However, these methods generally only offer technical information on the spatial distribution of disease risk itself, which may be incomplete for making decisions in a complex situation. In prioritizing surveillance and intervention strategies, decision-makers often also need to consider spatially explicit information on other important dimensions, such as the regional specificity of public acceptance, population vulnerability, resource availability, intervention effectiveness, and land use. There is a need for a unified strategy for supporting public health decision making that integrates available data for assessing spatially explicit disease risk, with other criteria, to implement effective prevention and control strategies. Multi-criteria decision analysis (MCDA) is a decision support tool that allows for the consideration of diverse quantitative and qualitative criteria using both data-driven and qualitative indicators for evaluating alternative strategies with transparency and stakeholder participation. Here we propose a MCDA-based approach to the development of geospatial models and spatially explicit decision support tools for the management of vector-borne diseases. We describe the conceptual framework that MCDA offers as well as technical considerations, approaches to implementation and expected outcomes. We conclude that MCDA is a powerful tool that offers tremendous potential for use in public health decision-making in general and vector-borne disease management in particular. PMID:22206355

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2008-09

USGS Publications Warehouse

,

2009-01-01

Geographic information system (GIS) technology has become an important tool for scientific investigation, resource management, and environmental planning. A GIS is a computer-aided system capable of collecting, storing, analyzing, and displaying spatially referenced digital data. GIS technology is useful for analyzing a wide variety of spatial data. Remote sensing involves collecting remotely sensed data, such as satellite imagery, aerial photography, or radar images, and analyzing the data to gather information or investigate trends about the environment or the Earth's surface. Spatial analysis combines remotely sensed, thematic, statistical, quantitative, and geographical data through overlay, modeling, and other analytical techniques to investigate specific research questions. It is the combination of data formats and analysis techniques that has made GIS an essential tool in scientific investigations. This fact sheet presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup during 2008 and 2009. After a summary of GIS Workgroup capabilities, brief descriptions of activities by project at the local and national levels are presented. Projects are grouped by the fiscal year (October-September 2008 or 2009) the project ends and include overviews, project images, and Internet links to additional project information and related publications or articles.

A geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling: GEOSTATISTICAL SENSITIVITY ANALYSIS

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

Dai, Heng; Chen, Xingyuan; Ye, Ming

Sensitivity analysis is an important tool for quantifying uncertainty in the outputs of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a hierarchical sensitivity analysis method that (1) constructs an uncertainty hierarchy by analyzing the input uncertainty sources, and (2) accounts for the spatial correlation among parameters at each level ofmore » the hierarchy using geostatistical tools. The contribution of uncertainty source at each hierarchy level is measured by sensitivity indices calculated using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport in model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally as driven by the dynamic interaction between groundwater and river water at the site. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed parameters.« less

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME.

PubMed

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2016-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments.

Making Space for Place: Mapping Tools and Practices to Teach for Spatial Justice

ERIC Educational Resources Information Center

Rubel, Laurie H.; Hall-Wieckert, Maren; Lim, Vivian Y.

2017-01-01

This article presents a set of spatial tools for classroom learning about spatial justice. As part of a larger team, we designed a curriculum that engaged 10 learners with 3 spatial tools: (a) an oversized floor map, (b) interactive geographic information systems (GIS) maps, and (c) participatory mapping. We analyze how these tools supported…

Infrastructure Analysis Tools: A Focus on Cash Flow Analysis (Presentation)

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

Melaina, M.; Penev, M.

2012-09-01

NREL has developed and maintains a variety of infrastructure analysis models for the U.S. Department of Energy. Business case analysis has recently been added to this tool set. This presentation focuses on cash flow analysis. Cash flows depend upon infrastructure costs, optimized spatially and temporally, and assumptions about financing and revenue. NREL has incorporated detailed metrics on financing and incentives into the models. Next steps in modeling include continuing to collect feedback on regional/local infrastructure development activities and 'roadmap' dynamics, and incorporating consumer preference assumptions on infrastructure to provide direct feedback between vehicles and station rollout.

Resource materials for a GIS spatial analysis course

USGS Publications Warehouse

Raines, Gary L.

2001-01-01

This report consists of materials prepared for a GIS spatial analysis course offered as part of the Geography curriculum at the University of Nevada, Reno and the University of California at Santa Barbara in the spring of 2000. The report is intended to share information with instructors preparing spatial-modeling training and scientists with advanced GIS expertise. The students taking this class had completed each universities GIS curriculum and had a foundation in statistics as part of a science major. This report is organized into chapters that contain the following: Slides used during lectures, Guidance on the use of Arcview, Introduction to filtering in Arcview, Conventional and spatial correlation in Arcview, Tools for fuzzification in Arcview, Data and instructions for creating using ArcSDM for simple weights-of-evidence, fuzzy logic, and neural network models for Carlin-type gold deposits in central Nevada, Reading list on spatial modeling, and Selected student spatial-modeling posters from the laboratory exercises.

Investigation and Evaluation of the open source ETL tools GeoKettle and Talend Open Studio in terms of their ability to process spatial data

NASA Astrophysics Data System (ADS)

Kuhnert, Kristin; Quedenau, Jörn

2016-04-01

Integration and harmonization of large spatial data sets is not only since the introduction of the spatial data infrastructure INSPIRE a big issue. The process of extracting and combining spatial data from heterogeneous source formats, transforming that data to obtain the required quality for particular purposes and loading it into a data store, are common tasks. The procedure of Extraction, Transformation and Loading of data is called ETL process. Geographic Information Systems (GIS) can take over many of these tasks but often they are not suitable for processing large datasets. ETL tools can make the implementation and execution of ETL processes convenient and efficient. One reason for choosing ETL tools for data integration is that they ease maintenance because of a clear (graphical) presentation of the transformation steps. Developers and administrators are provided with tools for identification of errors, analyzing processing performance and managing the execution of ETL processes. Another benefit of ETL tools is that for most tasks no or only little scripting skills are required so that also researchers without programming background can easily work with it. Investigations on ETL tools for business approaches are available for a long time. However, little work has been published on the capabilities of those tools to handle spatial data. In this work, we review and compare the open source ETL tools GeoKettle and Talend Open Studio in terms of processing spatial data sets of different formats. For evaluation, ETL processes are performed with both software packages based on air quality data measured during the BÄRLIN2014 Campaign initiated by the Institute for Advanced Sustainability Studies (IASS). The aim of the BÄRLIN2014 Campaign is to better understand the sources and distribution of particulate matter in Berlin. The air quality data are available in heterogeneous formats because they were measured with different instruments. For further data analysis, the instrument data has been complemented by other georeferenced data provided by the local environmental authorities. This includes both vector and raster data on e.g. land use categories or building heights, extracted from flat files and OGC-compliant web services. The requirements on the ETL tools are now for instance the extraction of different input datasets like Web Feature Services or vector datasets and the loading of those into databases. The tools also have to manage transformations on spatial datasets like to work with spatial functions (e.g. intersection, union) or change spatial reference systems. Preliminary results suggest that many complex transformation tasks could be accomplished with the existing set of components from both software tools, while there are still many gaps in the range of available features. Both ETL tools differ in functionality and in the way of implementation of various steps. For some tasks no predefined components are available at all, which could partly be compensated by the use of the respective API (freely configurable components in Java or JavaScript).

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

A topological multilayer model of the human body.

PubMed

Barbeito, Antonio; Painho, Marco; Cabral, Pedro; O'Neill, João

2015-11-04

Geographical information systems deal with spatial databases in which topological models are described with alphanumeric information. Its graphical interfaces implement the multilayer concept and provide powerful interaction tools. In this study, we apply these concepts to the human body creating a representation that would allow an interactive, precise, and detailed anatomical study. A vector surface component of the human body is built using a three-dimensional (3-D) reconstruction methodology. This multilayer concept is implemented by associating raster components with the corresponding vector surfaces, which include neighbourhood topology enabling spatial analysis. A root mean square error of 0.18 mm validated the three-dimensional reconstruction technique of internal anatomical structures. The expansion of the identification and the development of a neighbourhood analysis function are the new tools provided in this model.

Multi-scale imaging and informatics pipeline for in situ pluripotent stem cell analysis.

PubMed

Gorman, Bryan R; Lu, Junjie; Baccei, Anna; Lowry, Nathan C; Purvis, Jeremy E; Mangoubi, Rami S; Lerou, Paul H

2014-01-01

Human pluripotent stem (hPS) cells are a potential source of cells for medical therapy and an ideal system to study fate decisions in early development. However, hPS cells cultured in vitro exhibit a high degree of heterogeneity, presenting an obstacle to clinical translation. hPS cells grow in spatially patterned colony structures, necessitating quantitative single-cell image analysis. We offer a tool for analyzing the spatial population context of hPS cells that integrates automated fluorescent microscopy with an analysis pipeline. It enables high-throughput detection of colonies at low resolution, with single-cellular and sub-cellular analysis at high resolutions, generating seamless in situ maps of single-cellular data organized by colony. We demonstrate the tool's utility by analyzing inter- and intra-colony heterogeneity of hPS cell cycle regulation and pluripotency marker expression. We measured the heterogeneity within individual colonies by analyzing cell cycle as a function of distance. Cells loosely associated with the outside of the colony are more likely to be in G1, reflecting a less pluripotent state, while cells within the first pluripotent layer are more likely to be in G2, possibly reflecting a G2/M block. Our multi-scale analysis tool groups colony regions into density classes, and cells belonging to those classes have distinct distributions of pluripotency markers and respond differently to DNA damage induction. Lastly, we demonstrate that our pipeline can robustly handle high-content, high-resolution single molecular mRNA FISH data by using novel image processing techniques. Overall, the imaging informatics pipeline presented offers a novel approach to the analysis of hPS cells that includes not only single cell features but also colony wide, and more generally, multi-scale spatial configuration.

Open Source GIS based integrated watershed management

NASA Astrophysics Data System (ADS)

Byrne, J. M.; Lindsay, J.; Berg, A. A.

2013-12-01

Optimal land and water management to address future and current resource stresses and allocation challenges requires the development of state-of-the-art geomatics and hydrological modelling tools. Future hydrological modelling tools should be of high resolution, process based with real-time capability to assess changing resource issues critical to short, medium and long-term enviromental management. The objective here is to merge two renowned, well published resource modeling programs to create an source toolbox for integrated land and water management applications. This work will facilitate a much increased efficiency in land and water resource security, management and planning. Following an 'open-source' philosophy, the tools will be computer platform independent with source code freely available, maximizing knowledge transfer and the global value of the proposed research. The envisioned set of water resource management tools will be housed within 'Whitebox Geospatial Analysis Tools'. Whitebox, is an open-source geographical information system (GIS) developed by Dr. John Lindsay at the University of Guelph. The emphasis of the Whitebox project has been to develop a user-friendly interface for advanced spatial analysis in environmental applications. The plugin architecture of the software is ideal for the tight-integration of spatially distributed models and spatial analysis algorithms such as those contained within the GENESYS suite. Open-source development extends knowledge and technology transfer to a broad range of end-users and builds Canadian capability to address complex resource management problems with better tools and expertise for managers in Canada and around the world. GENESYS (Generate Earth Systems Science input) is an innovative, efficient, high-resolution hydro- and agro-meteorological model for complex terrain watersheds developed under the direction of Dr. James Byrne. GENESYS is an outstanding research and applications tool to address challenging resource management issues in industry, government and nongovernmental agencies. Current research and analysis tools were developed to manage meteorological, climatological, and land and water resource data efficiently at high resolution in space and time. The deliverable for this work is a Whitebox-GENESYS open-source resource management capacity with routines for GIS based watershed management including water in agriculture and food production. We are adding urban water management routines through GENESYS in 2013-15 with an engineering PhD candidate. Both Whitebox-GAT and GENESYS are already well-established tools. The proposed research will combine these products to create an open-source geomatics based water resource management tool that is revolutionary in both capacity and availability to a wide array of Canadian and global users

Kathleen Krah | NREL

Science.gov Websites

tool validation. Previous to joining NREL, her Masters thesis focused on a spatial analysis of strategies. Her undergraduate thesis focused on techno-economic and logistical cost modeling of offshore wind

Designing and Implementing an Online GIS Tool for Schools: The Finnish Case of the PaikkaOppi Project

ERIC Educational Resources Information Center

Riihelä, Juha; Mäki, Sanna

2015-01-01

This article describes initiatives implemented in Finland to create an online learning environment for studying geographic information systems (GIS). A development project produced an online GIS tool called PaikkaOppi, aimed at promoting GIS studies and spatial thinking skills in upper secondary schools. The project is reviewed through analysis of…

Comparison of Spatial Correlation Parameters between Full and Model Scale Launch Vehicles

NASA Technical Reports Server (NTRS)

Kenny, Jeremy; Giacomoni, Clothilde

2016-01-01

The current vibro-acoustic analysis tools require specific spatial correlation parameters as input to define the liftoff acoustic environment experienced by the launch vehicle. Until recently these parameters have not been very well defined. A comprehensive set of spatial correlation data were obtained during a scale model acoustic test conducted in 2014. From these spatial correlation data, several parameters were calculated: the decay coefficient, the diffuse to propagating ratio, and the angle of incidence. Spatial correlation data were also collected on the EFT-1 flight of the Delta IV vehicle which launched on December 5th, 2014. A comparison of the spatial correlation parameters from full scale and model scale data will be presented.

Making a Place for Space: Spatial Thinking in Social Science

PubMed Central

Logan, John R.

2013-01-01

New technologies and multilevel data sets that include geographic identifiers have heightened sociologists’ interest in spatial analysis. I review several of the key concepts, measures, and methods that are brought into play in this work, and offer examples of their application in a variety of substantive fields. I argue that the most effective use of the new tools requires greater emphasis on spatial thinking. A device as simple as an illustrative map requires some understanding of how people respond to visual cues; models as complex as HLM with spatial lags require thoughtful measurement decisions and raise questions about what a spatial effect represents. PMID:24273374

Raster Files for Utah Play Fairway Analysis

DOE Data Explorer

Wannamaker, Phil

2017-06-16

This submission contains raster files associated with several datasets that include earthquake density, Na/K geothermometers, fault density, heat flow, and gravity. Integrated together using spatial modeler tools in ArcGIS, these files can be used for play fairway analysis in regard to geothermal exploration.

A smarter way to search, share and utilize open-spatial online data for energy R&D - Custom machine learning and GIS tools in U.S. DOE's virtual data library & laboratory, EDX

NASA Astrophysics Data System (ADS)

Rose, K.; Bauer, J.; Baker, D.; Barkhurst, A.; Bean, A.; DiGiulio, J.; Jones, K.; Jones, T.; Justman, D.; Miller, R., III; Romeo, L.; Sabbatino, M.; Tong, A.

2017-12-01

As spatial datasets are increasingly accessible through open, online systems, the opportunity to use these resources to address a range of Earth system questions grows. Simultaneously, there is a need for better infrastructure and tools to find and utilize these resources. We will present examples of advanced online computing capabilities, hosted in the U.S. DOE's Energy Data eXchange (EDX), that address these needs for earth-energy research and development. In one study the computing team developed a custom, machine learning, big data computing tool designed to parse the web and return priority datasets to appropriate servers to develop an open-source global oil and gas infrastructure database. The results of this spatial smart search approach were validated against expert-driven, manual search results which required a team of seven spatial scientists three months to produce. The custom machine learning tool parsed online, open systems, including zip files, ftp sites and other web-hosted resources, in a matter of days. The resulting resources were integrated into a geodatabase now hosted for open access via EDX. Beyond identifying and accessing authoritative, open spatial data resources, there is also a need for more efficient tools to ingest, perform, and visualize multi-variate, spatial data analyses. Within the EDX framework, there is a growing suite of processing, analytical and visualization capabilities that allow multi-user teams to work more efficiently in private, virtual workspaces. An example of these capabilities are a set of 5 custom spatio-temporal models and data tools that form NETL's Offshore Risk Modeling suite that can be used to quantify oil spill risks and impacts. Coupling the data and advanced functions from EDX with these advanced spatio-temporal models has culminated with an integrated web-based decision-support tool. This platform has capabilities to identify and combine data across scales and disciplines, evaluate potential environmental, social, and economic impacts, highlight knowledge or technology gaps, and reduce uncertainty for a range of `what if' scenarios relevant to oil spill prevention efforts. These examples illustrate EDX's growing capabilities for advanced spatial data search and analysis to support geo-data science needs.

Building energy analysis tool

DOEpatents

Brackney, Larry; Parker, Andrew; Long, Nicholas; Metzger, Ian; Dean, Jesse; Lisell, Lars

2016-04-12

A building energy analysis system includes a building component library configured to store a plurality of building components, a modeling tool configured to access the building component library and create a building model of a building under analysis using building spatial data and using selected building components of the plurality of building components stored in the building component library, a building analysis engine configured to operate the building model and generate a baseline energy model of the building under analysis and further configured to apply one or more energy conservation measures to the baseline energy model in order to generate one or more corresponding optimized energy models, and a recommendation tool configured to assess the one or more optimized energy models against the baseline energy model and generate recommendations for substitute building components or modifications.

Research on the EDM Technology for Micro-holes at Complex Spatial Locations

NASA Astrophysics Data System (ADS)

Y Liu, J.; Guo, J. M.; Sun, D. J.; Cai, Y. H.; Ding, L. T.; Jiang, H.

2017-12-01

For the demands on machining micro-holes at complex spatial location, several key technical problems are conquered such as micro-Electron Discharge Machining (micro-EDM) power supply system’s development, the host structure’s design and machining process technical. Through developing low-voltage power supply circuit, high-voltage circuit, micro and precision machining circuit and clearance detection system, the narrow pulse and high frequency six-axis EDM machining power supply system is developed to meet the demands on micro-hole discharging machining. With the method of combining the CAD structure design, CAE simulation analysis, modal test, ODS (Operational Deflection Shapes) test and theoretical analysis, the host construction and key axes of the machine tool are optimized to meet the position demands of the micro-holes. Through developing the special deionized water filtration system to make sure that the machining process is stable enough. To verify the machining equipment and processing technical developed in this paper through developing the micro-hole’s processing flow and test on the real machine tool. As shown in the final test results: the efficient micro-EDM machining pulse power supply system, machine tool host system, deionized filtration system and processing method developed in this paper meet the demands on machining micro-holes at complex spatial locations.

Further investigations on fixed abrasive diamond pellets used for diminishing mid-spatial frequency errors of optical mirrors.

PubMed

Dong, Zhichao; Cheng, Haobo; Tam, Hon-Yuen

2014-01-20

As further application investigations on fixed abrasive diamond pellets (FADPs), this work exhibits their potential capability for diminishing mid-spatial frequency errors (MSFEs, i.e., periodic small structure) of optical surfaces. Benefitting from its high surficial rigidness, the FADPs tool has a natural smoothing effect to periodic small errors. Compared with the previous design, this proposed new tool employs more compliance to aspherical surfaces due to the pellets being mutually separated and bonded on a steel plate with elastic back of silica rubber adhesive. Moreover, a unicursal Peano-like path is presented for improving MSFEs, which can enhance the multidirectionality and uniformity of the tool's motion. Experiments were conducted to validate the effectiveness of FADPs for diminishing MSFEs. In the lapping of a Φ=420 mm Zerodur paraboloid workpiece, the grinding ripples were quickly diminished (210 min) by both visual inspection and profile metrology, as well as the power spectrum density (PSD) analysis, RMS was reduced from 4.35 to 0.55 μm. In the smoothing of a Φ=101 mm fused silica workpiece, MSFEs were obviously improved from the inspection of surface form maps, interferometric fringe patterns, and PSD analysis. The mid-spatial frequency RMS was diminished from 0.017λ to 0.014λ (λ=632.8 nm).

'spup' - an R package for uncertainty propagation analysis in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2017-04-01

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. Currently, advances in uncertainty propagation and assessment have been paralleled by a growing number of software tools for uncertainty analysis, but none has gained recognition for a universal applicability and being able to deal with 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 (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Land-use planning of Volyn region (Ukraine) using Geographic Information Systems (GIS) technologies

NASA Astrophysics Data System (ADS)

Strielko, Irina; Pereira, Paulo

2014-05-01

Land-use development planning is carried out in order to create a favourable environment for human life, sustainable socioeconomic and spatial development. Landscape planning is an important part of land-use development that aims to meet the fundamental principles of sustainable development. Geographic Information Systems (GIS) is a fundamental tool to make a better landscape planning at different territorial levels, providing data and maps to support decision making. The objective of this work is to create spatio-temporal, territorial and ecological model of development of Volyn region (Ukraine). It is based on existing spatial raster and vector data and includes the analysis of territory dynamics as the aspects responsible for it. A spatial analyst tool was used to zone the areas according to their environmental components and economic activity. This analysis is fundamental to define the basic parameters of sustainability of Volyn region. To carry out this analysis, we determined the demographic capacity of districts and the analysis of spatial parameters of land use. On the basis of the existing natural resources, we observed that there is a need of landscape protection and integration of more are natural areas in the Pan-European Ecological Network. Using GIS technologies to landscape planning in Volyn region, allowed us to identify, natural areas of interest, contribute to a better resource management and conflict resolution. Geographic Information Systems will help to formulate and implement landscape policies, reform the existing administrative system of Volyn region and contribute to a better sustainable development.

Visualizing driving forces of spatially extended systems using the recurrence plot framework

NASA Astrophysics Data System (ADS)

Riedl, Maik; Marwan, Norbert; Kurths, Jürgen

2017-12-01

The increasing availability of highly resolved spatio-temporal data leads to new opportunities as well as challenges in many scientific disciplines such as climatology, ecology or epidemiology. This allows more detailed insights into the investigated spatially extended systems. However, this development needs advanced techniques of data analysis which go beyond standard linear tools since the more precise consideration often reveals nonlinear phenomena, for example threshold effects. One of these tools is the recurrence plot approach which has been successfully applied to the description of complex systems. Using this technique's power of visualization, we propose the analysis of the local minima of the underlying distance matrix in order to display driving forces of spatially extended systems. The potential of this novel idea is demonstrated by the analysis of the chlorophyll concentration and the sea surface temperature in the Southern California Bight. We are able not only to confirm the influence of El Niño events on the phytoplankton growth in this region but also to confirm two discussed regime shifts in the California current system. This new finding underlines the power of the proposed approach and promises new insights into other complex systems.

Spatial pattern recognition of seismic events in South West Colombia

NASA Astrophysics Data System (ADS)

Benítez, Hernán D.; Flórez, Juan F.; Duque, Diana P.; Benavides, Alberto; Lucía Baquero, Olga; Quintero, Jiber

2013-09-01

Recognition of seismogenic zones in geographical regions supports seismic hazard studies. This recognition is usually based on visual, qualitative and subjective analysis of data. Spatial pattern recognition provides a well founded means to obtain relevant information from large amounts of data. The purpose of this work is to identify and classify spatial patterns in instrumental data of the South West Colombian seismic database. In this research, clustering tendency analysis validates whether seismic database possesses a clustering structure. A non-supervised fuzzy clustering algorithm creates groups of seismic events. Given the sensitivity of fuzzy clustering algorithms to centroid initial positions, we proposed a methodology to initialize centroids that generates stable partitions with respect to centroid initialization. As a result of this work, a public software tool provides the user with the routines developed for clustering methodology. The analysis of the seismogenic zones obtained reveals meaningful spatial patterns in South-West Colombia. The clustering analysis provides a quantitative location and dispersion of seismogenic zones that facilitates seismological interpretations of seismic activities in South West Colombia.

A web-based tool for groundwater mapping and drought analysis

NASA Astrophysics Data System (ADS)

Christensen, S.; Burns, M.; Jones, N.; Strassberg, G.

2012-12-01

In 2011-2012, the state of Texas saw the worst one-year drought on record. Fluctuations in gravity measured by GRACE satellites indicate that as much as 100 cubic kilometers of water was lost during this period. Much of this came from reservoirs and shallow soil moisture, but a significant amount came from aquifers. In response to this crisis, a Texas Drought Technology Steering Committee (TDTSC) consisting of academics and water managers was formed to develop new tools and strategies to assist the state in monitoring, predicting, and responding to drought events. In this presentation, we describe one of the tools that was developed as part of this effort. When analyzing the impact of drought on groundwater levels, it is fairly common to examine time series data at selected monitoring wells. However, accurately assessing impacts and trends requires both spatial and temporal analysis involving the development of detailed water level maps at various scales. Creating such maps in a flexible and rapid fashion is critical for effective drought analysis, but can be challenging due to the massive amounts of data involved and the processing required to generate such maps. Furthermore, wells are typically not sampled at the same points in time, and so developing a water table map for a particular date requires both spatial and temporal interpolation of water elevations. To address this challenge, a Cloud-based water level mapping system was developed for the state of Texas. The system is based on the Texas Water Development Board (TWDB) groundwater database, but can be adapted to use other databases as well. The system involves a set of ArcGIS workflows running on a server with a web-based front end and a Google Earth plug-in. A temporal interpolation geoprocessing tool was developed to estimate the piezometric heads for all wells in a given region at a specific date using a regression analysis. This interpolation tool is coupled with other geoprocessing tools to filter data and interpolate point elevations spatially to produce water level, drawdown, and depth to groundwater maps. The web interface allows for users to generate these maps at locations and times of interest. A sequence of maps can be generated over a period of time and animated to visualize how water levels are changing. The time series regression analysis can also be used to do short-term predictions of future water levels.

Nonverbal communication in doctor-elderly patient transactions (NDEPT): development of a tool.

PubMed

Gorawara-Bhat, Rita; Cook, Mary Ann; Sachs, Greg A

2007-05-01

There are several measurement tools to assess verbal dimensions in clinical encounters; in contrast, there is no established tool to evaluate physical nonverbal dimensions in geriatric encounters. The present paper describes the development of a tool to assess the physical context of exam rooms in doctor-older patient visits. Salient features of the tool were derived from the medical literature and systematic observations of videotapes and refined during current research. The tool consists of two main dimensions of exam rooms: (1) physical dimensions comprising static and dynamic attributes that become operational through the spatial configuration and can influence the manifestation of (2) kinesic attributes. Details of the coding form and inter-rater reliability are presented. The usefulness of the tool is demonstrated through an analysis of 50 National Institute of Aging videotapes. Physicians in exam rooms with no desk in the interaction, no height difference and optimal interaction distance were observed to have greater eye contact and touch than physicians' in exam rooms with a desk, similar height difference and interaction distance. The tool can enable physicians to assess the spatial configuration of exam rooms (through Parts A and B) and thus facilitate the structuring of kinesic attributes (Part C).

Brazilian spatial dynamics in the long term (1872-2000): ``path dependency'' or ``reversal of fortune''?

NASA Astrophysics Data System (ADS)

Monasterio, Leonardo Monteiro

2010-03-01

This paper analyzes the spatial dynamics of Brazilian regional inequalities between 1872 and 2000 using contemporary tools. The first part of the paper provides new estimates of income per capita in 1872 by municipality using census and electoral information on income by occupation. The level of analysis is the Minimum Comparable Areas 1872-2000 developed by Reis et al. (Áreas mínimas comparáveis para os períodos intercensitários de 1872 a 2000, 2007). These areas are the least aggregation of adjacent municipalities required to allow consistent geographic area comparisons between census years. In the second section of the paper, Exploratory Spatial Data Analysis, Markov chains and stochastic kernel techniques (spatially conditioned) are applied to the dataset. The results suggest that, in broad terms, the spatial pattern of income distribution in Brazil during that period of time has remained stable.

Visualization, documentation, analysis, and communication of large scale gene regulatory networks

PubMed Central

Longabaugh, William J.R.; Davidson, Eric H.; Bolouri, Hamid

2009-01-01

Summary Genetic regulatory networks (GRNs) are complex, large-scale, and spatially and temporally distributed. These characteristics impose challenging demands on computational GRN modeling tools, and there is a need for custom modeling tools. In this paper, we report on our ongoing development of BioTapestry, an open source, freely available computational tool designed specifically for GRN modeling. We also outline our future development plans, and give some examples of current applications of BioTapestry. PMID:18757046

Bioenergy Knowledge Discovery Framework Fact Sheet

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

None

The Bioenergy Knowledge Discovery Framework (KDF) supports the development of a sustainable bioenergy industry by providing access to a variety of data sets, publications, and collaboration and mapping tools that support bioenergy research, analysis, and decision making. In the KDF, users can search for information, contribute data, and use the tools and map interface to synthesize, analyze, and visualize information in a spatially integrated manner.

Using GIS to analyze animal movements in the marine environment

USGS Publications Warehouse

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

2001-01-01

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

Environmental Assessment and Monitoring with ICAMS (Image Characterization and Modeling System) Using Multiscale Remote-Sensing Data

NASA Technical Reports Server (NTRS)

Lam, N.; Qiu, H.-I.; Quattrochi, Dale A.; Zhao, Wei

1997-01-01

With the rapid increase in spatial data, especially in the NASA-EOS (Earth Observing System) era, it is necessary to develop efficient and innovative tools to handle and analyze these data so that environmental conditions can be assessed and monitored. A main difficulty facing geographers and environmental scientists in environmental assessment and measurement is that spatial analytical tools are not easily accessible. We have recently developed a remote sensing/GIS software module called Image Characterization and Modeling System (ICAMS) to provide specialized spatial analytical tools for the measurement and characterization of satellite and other forms of spatial data. ICAMS runs on both the Intergraph-MGE and Arc/info UNIX and Windows-NT platforms. The main techniques in ICAMS include fractal measurement methods, variogram analysis, spatial autocorrelation statistics, textural measures, aggregation techniques, normalized difference vegetation index (NDVI), and delineation of land/water and vegetated/non-vegetated boundaries. In this paper, we demonstrate the main applications of ICAMS on the Intergraph-MGE platform using Landsat Thematic Mapper images from the city of Lake Charles, Louisiana. While the utilities of ICAMS' spatial measurement methods (e.g., fractal indices) in assessing environmental conditions remain to be researched, making the software available to a wider scientific community can permit the techniques in ICAMS to be evaluated and used for a diversity of applications. The findings from these various studies should lead to improved algorithms and more reliable models for environmental assessment and monitoring.

mizuRoute version 1: A river network routing tool for a continental domain water resources applications

USGS Publications Warehouse

Mizukami, Naoki; Clark, Martyn P.; Sampson, Kevin; Nijssen, Bart; Mao, Yixin; McMillan, Hilary; Viger, Roland; Markstrom, Steven; Hay, Lauren E.; Woods, Ross; Arnold, Jeffrey R.; Brekke, Levi D.

2016-01-01

This paper describes the first version of a stand-alone runoff routing tool, mizuRoute. The mizuRoute tool post-processes runoff outputs from any distributed hydrologic model or land surface model to produce spatially distributed streamflow at various spatial scales from headwater basins to continental-wide river systems. The tool can utilize both traditional grid-based river network and vector-based river network data. Both types of river network include river segment lines and the associated drainage basin polygons, but the vector-based river network can represent finer-scale river lines than the grid-based network. Streamflow estimates at any desired location in the river network can be easily extracted from the output of mizuRoute. The routing process is simulated as two separate steps. First, hillslope routing is performed with a gamma-distribution-based unit-hydrograph to transport runoff from a hillslope to a catchment outlet. The second step is river channel routing, which is performed with one of two routing scheme options: (1) a kinematic wave tracking (KWT) routing procedure; and (2) an impulse response function – unit-hydrograph (IRF-UH) routing procedure. The mizuRoute tool also includes scripts (python, NetCDF operators) to pre-process spatial river network data. This paper demonstrates mizuRoute's capabilities to produce spatially distributed streamflow simulations based on river networks from the United States Geological Survey (USGS) Geospatial Fabric (GF) data set in which over 54 000 river segments and their contributing areas are mapped across the contiguous United States (CONUS). A brief analysis of model parameter sensitivity is also provided. The mizuRoute tool can assist model-based water resources assessments including studies of the impacts of climate change on streamflow.

MOLNs: A CLOUD PLATFORM FOR INTERACTIVE, REPRODUCIBLE, AND SCALABLE SPATIAL STOCHASTIC COMPUTATIONAL EXPERIMENTS IN SYSTEMS BIOLOGY USING PyURDME

PubMed Central

Drawert, Brian; Trogdon, Michael; Toor, Salman; Petzold, Linda; Hellander, Andreas

2017-01-01

Computational experiments using spatial stochastic simulations have led to important new biological insights, but they require specialized tools and a complex software stack, as well as large and scalable compute and data analysis resources due to the large computational cost associated with Monte Carlo computational workflows. The complexity of setting up and managing a large-scale distributed computation environment to support productive and reproducible modeling can be prohibitive for practitioners in systems biology. This results in a barrier to the adoption of spatial stochastic simulation tools, effectively limiting the type of biological questions addressed by quantitative modeling. In this paper, we present PyURDME, a new, user-friendly spatial modeling and simulation package, and MOLNs, a cloud computing appliance for distributed simulation of stochastic reaction-diffusion models. MOLNs is based on IPython and provides an interactive programming platform for development of sharable and reproducible distributed parallel computational experiments. PMID:28190948

Geostatistics: a common link between medical geography, mathematical geology, and medical geology

PubMed Central

Goovaerts, P.

2015-01-01

Synopsis Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential ‘causes’ of disease, such as environmental exposure, diet and unhealthy behaviours, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentration across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level. PMID:25722963

Geostatistics: a common link between medical geography, mathematical geology, and medical geology.

PubMed

Goovaerts, P

2014-08-01

Since its development in the mining industry, geostatistics has emerged as the primary tool for spatial data analysis in various fields, ranging from earth and atmospheric sciences to agriculture, soil science, remote sensing, and more recently environmental exposure assessment. In the last few years, these tools have been tailored to the field of medical geography or spatial epidemiology, which is concerned with the study of spatial patterns of disease incidence and mortality and the identification of potential 'causes' of disease, such as environmental exposure, diet and unhealthy behaviours, economic or socio-demographic factors. On the other hand, medical geology is an emerging interdisciplinary scientific field studying the relationship between natural geological factors and their effects on human and animal health. This paper provides an introduction to the field of medical geology with an overview of geostatistical methods available for the analysis of geological and health data. Key concepts are illustrated using the mapping of groundwater arsenic concentration across eleven Michigan counties and the exploration of its relationship to the incidence of prostate cancer at the township level.

Time and space in the middle paleolithic: Spatial structure and occupation dynamics of seven open-air sites.

PubMed

Clark, Amy E

2016-05-06

The spatial structure of archeological sites can help reconstruct the settlement dynamics of hunter-gatherers by providing information on the number and length of occupations. This study seeks to access this information through a comparison of seven sites. These sites are open-air and were all excavated over large spatial areas, up to 2,000 m(2) , and are therefore ideal for spatial analysis, which was done using two complementary methods, lithic refitting and density zones. Both methods were assessed statistically using confidence intervals. The statistically significant results from each site were then compiled to evaluate trends that occur across the seven sites. These results were used to assess the "spatial consistency" of each assemblage and, through that, the number and duration of occupations. This study demonstrates that spatial analysis can be a powerful tool in research on occupation dynamics and can help disentangle the many occupations that often make up an archeological assemblage. © 2016 Wiley Periodicals, Inc.

Linking Automated Data Analysis and Visualization with Applications in Developmental Biology and High-Energy Physics

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

Ruebel, Oliver

2009-11-20

Knowledge discovery from large and complex collections of today's scientific datasets is a challenging task. With the ability to measure and simulate more processes at increasingly finer spatial and temporal scales, the increasing number of data dimensions and data objects is presenting tremendous challenges for data analysis and effective data exploration methods and tools. Researchers are overwhelmed with data and standard tools are often insufficient to enable effective data analysis and knowledge discovery. The main objective of this thesis is to provide important new capabilities to accelerate scientific knowledge discovery form large, complex, and multivariate scientific data. The research coveredmore » in this thesis addresses these scientific challenges using a combination of scientific visualization, information visualization, automated data analysis, and other enabling technologies, such as efficient data management. The effectiveness of the proposed analysis methods is demonstrated via applications in two distinct scientific research fields, namely developmental biology and high-energy physics.Advances in microscopy, image analysis, and embryo registration enable for the first time measurement of gene expression at cellular resolution for entire organisms. Analysis of high-dimensional spatial gene expression datasets is a challenging task. By integrating data clustering and visualization, analysis of complex, time-varying, spatial gene expression patterns and their formation becomes possible. The analysis framework MATLAB and the visualization have been integrated, making advanced analysis tools accessible to biologist and enabling bioinformatic researchers to directly integrate their analysis with the visualization. Laser wakefield particle accelerators (LWFAs) promise to be a new compact source of high-energy particles and radiation, with wide applications ranging from medicine to physics. To gain insight into the complex physical processes of particle acceleration, physicists model LWFAs computationally. The datasets produced by LWFA simulations are (i) extremely large, (ii) of varying spatial and temporal resolution, (iii) heterogeneous, and (iv) high-dimensional, making analysis and knowledge discovery from complex LWFA simulation data a challenging task. To address these challenges this thesis describes the integration of the visualization system VisIt and the state-of-the-art index/query system FastBit, enabling interactive visual exploration of extremely large three-dimensional particle datasets. Researchers are especially interested in beams of high-energy particles formed during the course of a simulation. This thesis describes novel methods for automatic detection and analysis of particle beams enabling a more accurate and efficient data analysis process. By integrating these automated analysis methods with visualization, this research enables more accurate, efficient, and effective analysis of LWFA simulation data than previously possible.« less

GIS Tools For Improving Pedestrian & Bicycle Safety

DOT National Transportation Integrated Search

2000-07-01

Geographic Information System (GIS) software turns statistical data, such as accidents, and geographic data, such as roads and crash locations, into meaningful information for spatial analysis and mapping. In this project, GIS-based analytical techni...

A computational study on outliers in world music.

PubMed

Panteli, Maria; Benetos, Emmanouil; Dixon, Simon

2017-01-01

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as 'outliers'. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the 'uniqueness' of the music of each country.

A computational study on outliers in world music

PubMed Central

Benetos, Emmanouil; Dixon, Simon

2017-01-01

The comparative analysis of world music cultures has been the focus of several ethnomusicological studies in the last century. With the advances of Music Information Retrieval and the increased accessibility of sound archives, large-scale analysis of world music with computational tools is today feasible. We investigate music similarity in a corpus of 8200 recordings of folk and traditional music from 137 countries around the world. In particular, we aim to identify music recordings that are most distinct compared to the rest of our corpus. We refer to these recordings as ‘outliers’. We use signal processing tools to extract music information from audio recordings, data mining to quantify similarity and detect outliers, and spatial statistics to account for geographical correlation. Our findings suggest that Botswana is the country with the most distinct recordings in the corpus and China is the country with the most distinct recordings when considering spatial correlation. Our analysis includes a comparison of musical attributes and styles that contribute to the ‘uniqueness’ of the music of each country. PMID:29253027

Geoinformatic subsystem for real estate market analysis). (Polish Title: Podsystem geoinformatyczny do analizy rynku nieruchomosci)

NASA Astrophysics Data System (ADS)

Basista, A.

2013-12-01

There are many tools to manage spatial data. They called Geographic Information System (GIS), which apart from data visualization in space, let users make various spatial analysis. Thanks to them, it is possible to obtain more, essential information for real estate market analysis. Many scientific research present GIS exploitation to future mass valuation, because it is necessary to use advanced tools to manage such a huge real estates' data sets gathered for mass valuation needs. In practice, appraisers use rarely these tools for single valuation, because there are not many available GIS tools to support real estate valuation. The paper presents the functionality of geoinformatic subsystem, that is used to support real estate market analysis and real estate valuation. There are showed a detailed description of the process relied to attributes' inputting into the database and the attributes' values calculation based on the proposed definition of attributes' scales. This work presents also the algorithm of similar properties selection that was implemented within the described subsystem. The main stage of this algorithm is the calculation of the price creative indicator for each real estate, using their attributes' values. The set of properties, chosen in this way, are visualized on the map. The geoinformatic subsystem is used for the un-built real estates and living premises. Geographic Information System software was used to worked out this project. The basic functionality of gvSIG software (open source software) was extended and some extra functions were added to support real estate market analysis.

An integrated GIS application system for soil moisture data assimilation

NASA Astrophysics Data System (ADS)

Wang, Di; Shen, Runping; Huang, Xiaolong; Shi, Chunxiang

2014-11-01

The gaps in knowledge and existing challenges in precisely describing the land surface process make it critical to represent the massive soil moisture data visually and mine the data for further research.This article introduces a comprehensive soil moisture assimilation data analysis system, which is instructed by tools of C#, IDL, ArcSDE, Visual Studio 2008 and SQL Server 2005. The system provides integrated service, management of efficient graphics visualization and analysis of land surface data assimilation. The system is not only able to improve the efficiency of data assimilation management, but also comprehensively integrate the data processing and analysis tools into GIS development environment. So analyzing the soil moisture assimilation data and accomplishing GIS spatial analysis can be realized in the same system. This system provides basic GIS map functions, massive data process and soil moisture products analysis etc. Besides,it takes full advantage of a spatial data engine called ArcSDE to effeciently manage, retrieve and store all kinds of data. In the system, characteristics of temporal and spatial pattern of soil moiture will be plotted. By analyzing the soil moisture impact factors, it is possible to acquire the correlation coefficients between soil moisture value and its every single impact factor. Daily and monthly comparative analysis of soil moisture products among observations, simulation results and assimilations can be made in this system to display the different trends of these products. Furthermore, soil moisture map production function is realized for business application.

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

PubMed Central

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

2010-01-01

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

First GIS Analysis of Modern Stone Tools Used by Wild Chimpanzees (Pan troglodytes verus) in Bossou, Guinea, West Africa

PubMed Central

Arroyo, Adrian; Matsuzawa, Tetsuro; de la Torre, Ignacio

2015-01-01

Stone tool use by wild chimpanzees of West Africa offers a unique opportunity to explore the evolutionary roots of technology during human evolution. However, detailed analyses of chimpanzee stone artifacts are still lacking, thus precluding a comparison with the earliest archaeological record. This paper presents the first systematic study of stone tools used by wild chimpanzees to crack open nuts in Bossou (Guinea-Conakry), and applies pioneering analytical techniques to such artifacts. Automatic morphometric GIS classification enabled to create maps of use wear over the stone tools (anvils, hammers, and hammers/ anvils), which were blind tested with GIS spatial analysis of damage patterns identified visually. Our analysis shows that chimpanzee stone tool use wear can be systematized and specific damage patterns discerned, allowing to discriminate between active and passive pounders in lithic assemblages. In summary, our results demonstrate the heuristic potential of combined suites of GIS techniques for the analysis of battered artifacts, and have enabled creating a referential framework of analysis in which wild chimpanzee battered tools can for the first time be directly compared to the early archaeological record. PMID:25793642

Multifractal analysis of mobile social networks

NASA Astrophysics Data System (ADS)

Zheng, Wei; Zhang, Zifeng; Deng, Yufan

2017-09-01

As Wireless Fidelity (Wi-Fi)-enabled handheld devices have been widely used, the mobile social networks (MSNs) has been attracting extensive attention. Fractal approaches have also been widely applied to characterierize natural networks as useful tools to depict their spatial distribution and scaling properties. Moreover, when the complexity of the spatial distribution of MSNs cannot be properly charaterized by single fractal dimension, multifractal analysis is required. For further research, we introduced a multifractal analysis method based on box-covering algorithm to describe the structure of MSNs. Using this method, we find that the networks are multifractal at different time interval. The simulation results demonstrate that the proposed method is efficient for analyzing the multifractal characteristic of MSNs, which provides a distribution of singularities adequately describing both the heterogeneity of fractal patterns and the statistics of measurements across spatial scales in MSNs.

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).

Airborne Turbulence Detection System Certification Tool Set

NASA Technical Reports Server (NTRS)

Hamilton, David W.; Proctor, Fred H.

2006-01-01

A methodology and a corresponding set of simulation tools for testing and evaluating turbulence detection sensors has been presented. The tool set is available to industry and the FAA for certification of radar based airborne turbulence detection systems. The tool set consists of simulated data sets representing convectively induced turbulence, an airborne radar simulation system, hazard tables to convert the radar observable to an aircraft load, documentation, a hazard metric "truth" algorithm, and criteria for scoring the predictions. Analysis indicates that flight test data supports spatial buffers for scoring detections. Also, flight data and demonstrations with the tool set suggest the need for a magnitude buffer.

Using geostatistics to evaluate cleanup goals

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

Marcon, M.F.; Hopkins, L.P.

1995-12-01

Geostatistical analysis is a powerful predictive tool typically used to define spatial variability in environmental data. The information from a geostatistical analysis using kriging, a geostatistical. tool, can be taken a step further to optimize sampling location and frequency and help quantify sampling uncertainty in both the remedial investigation and remedial design at a hazardous waste site. Geostatistics were used to quantify sampling uncertainty in attainment of a risk-based cleanup goal and determine the optimal sampling frequency necessary to delineate the horizontal extent of impacted soils at a Gulf Coast waste site.

iGlobe Interactive Visualization and Analysis of Spatial Data

NASA Technical Reports Server (NTRS)

Hogan, Patrick

2012-01-01

iGlobe is open-source software built on NASA World Wind virtual globe technology. iGlobe provides a growing set of tools for weather science, climate research, and agricultural analysis. Up until now, these types of sophisticated tools have been developed in isolation by national agencies, academic institutions, and research organizations. By providing an open-source solution to analyze and visualize weather, climate, and agricultural data, the scientific and research communities can more readily advance solutions needed to understand better the dynamics of our home planet, Earth

Modeling the Spatial Dynamics of Regional Land Use: The CLUE-S Model

NASA Astrophysics Data System (ADS)

Verburg, Peter H.; Soepboer, Welmoed; Veldkamp, A.; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S. A.

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Modeling the spatial dynamics of regional land use: the CLUE-S model.

PubMed

Verburg, Peter H; Soepboer, Welmoed; Veldkamp, A; Limpiada, Ramil; Espaldon, Victoria; Mastura, Sharifah S A

2002-09-01

Land-use change models are important tools for integrated environmental management. Through scenario analysis they can help to identify near-future critical locations in the face of environmental change. A dynamic, spatially explicit, land-use change model is presented for the regional scale: CLUE-S. The model is specifically developed for the analysis of land use in small regions (e.g., a watershed or province) at a fine spatial resolution. The model structure is based on systems theory to allow the integrated analysis of land-use change in relation to socio-economic and biophysical driving factors. The model explicitly addresses the hierarchical organization of land use systems, spatial connectivity between locations and stability. Stability is incorporated by a set of variables that define the relative elasticity of the actual land-use type to conversion. The user can specify these settings based on expert knowledge or survey data. Two applications of the model in the Philippines and Malaysia are used to illustrate the functioning of the model and its validation.

Pattern detection in stream networks: Quantifying spatialvariability in fish distribution

USGS Publications Warehouse

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

2004-01-01

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

[Progress in the application of laser ablation ICP-MS to surface microanalysis in material science].

PubMed

Zhang, Yong; Jia, Yun-hai; Chen, Ji-wen; Shen, Xue-jing; Liu, Ying; Zhao, Leiz; Li, Dong-ling; Hang, Peng-cheng; Zhao, Zhen; Fan, Wan-lun; Wang, Hai-zhou

2014-08-01

In the present paper, apparatus and theory of surface analysis is introduced, and the progress in the application of laser ablation ICP-MS to microanalysis in ferrous, nonferrous and semiconductor field is reviewed in detail. Compared with traditional surface analytical tools, such as SEM/EDS (scanning electron microscopy/energy dispersive spectrum), EPMA (electron probe microanalysis analysis), AES (auger energy spectrum), etc. the advantage is little or no sample preparation, adjustable spatial resolution according to analytical demand, multi-element analysis and high sensitivity. It is now a powerful complementary method to traditional surface analytical tool. With the development of LA-ICP-MS technology maturing, more and more analytical workers will use this powerful tool in the future, and LA-ICP-MS will be a super star in elemental analysis field just like LIBS (Laser-induced breakdown spectroscopy).

Reply: Comparison of slope instability screening tools following a large storm event and application to forest management and policy

NASA Astrophysics Data System (ADS)

Whittaker, Kara A.; McShane, Dan

2013-02-01

A large storm event in southwest Washington State triggered over 2500 landslides and provided an opportunity to assess two slope stability screening tools. The statistical analysis conducted demonstrated that both screening tools are effective at predicting where landslides were likely to take place (Whittaker and McShane, 2012). Here we reply to two discussions of this article related to the development of the slope stability screening tools and the accuracy and scale of the spatial data used. Neither of the discussions address our statistical analysis or results. We provide greater detail on our sampling criteria and also elaborate on the policy and management implications of our findings and how they complement those of a separate investigation of landslides resulting from the same storm. The conclusions made in Whittaker and McShane (2012) stand as originally published unless future analysis indicates otherwise.

a Buffer Analysis Based on Co-Location Algorithm

NASA Astrophysics Data System (ADS)

Zhou, G.; Huang, S.; Wang, H.; Zhang, R.; Wang, Q.; Sha, H.; Liu, X.; Pan, Q.

2018-05-01

Buffer analysis is a common tool of spatial analysis, which deals with the problem of proximity in GIS. Buffer analysis researches the relationship between the center object and other objects around a certain distance. Buffer analysis can make the complicated problem be more scientifically and visually, and provide valuable information for users. Over the past decades, people have done a lot of researches on buffer analysis. Along with the constantly improvement of spatial analysis accuracy needed by people, people hope that the results of spatial analysis can be more exactly express the actual situation. Due to the influence of some certain factors, the impact scope and contact range of a geographic elements on the surrounding objects are uncertain. As all we know, each object has its own characteristics and changing rules in the nature. They are both independent and relative to each other. However, almost all the generational algorithms of existing buffer analysis are based on fixed buffer distance, which do not consider the co-location relationship among instances. Consequently, it is a waste of resource to retrieve the useless information, and useful information is ignored.

Using Enabling Technologies to Facilitate the Comparison of Satellite Observations with the Model Forecasts for Hurricane Study

NASA Astrophysics Data System (ADS)

Li, P.; Knosp, B.; Hristova-Veleva, S. M.; Niamsuwan, N.; Johnson, M. P.; Shen, T. P. J.; Tanelli, S.; Turk, J.; Vu, Q. A.

2014-12-01

Due to their complexity and volume, the satellite data are underutilized in today's hurricane research and operations. To better utilize these data, we developed the JPL Tropical Cyclone Information System (TCIS) - an Interactive Data Portal providing fusion between Near-Real-Time satellite observations and model forecasts to facilitate model evaluation and improvement. We have collected satellite observations and model forecasts in the Atlantic Basin and the East Pacific for the hurricane seasons since 2010 and supported the NASA Airborne Campaigns for Hurricane Study such as the Genesis and Rapid Intensification Processes (GRIP) in 2010 and the Hurricane and Severe Storm Sentinel (HS3) from 2012 to 2014. To enable the direct inter-comparisons of the satellite observations and the model forecasts, the TCIS was integrated with the NASA Earth Observing System Simulator Suite (NEOS3) to produce synthetic observations (e.g. simulated passive microwave brightness temperatures) from a number of operational hurricane forecast models (HWRF and GFS). An automated process was developed to trigger NEOS3 simulations via web services given the location and time of satellite observations, monitor the progress of the NEOS3 simulations, display the synthetic observation and ingest them into the TCIS database when they are done. In addition, three analysis tools, the joint PDF analysis of the brightness temperatures, ARCHER for finding the storm-center and the storm organization and the Wave Number Analysis tool for storm asymmetry and morphology analysis were integrated into TCIS to provide statistical and structural analysis on both observed and synthetic data. Interactive tools were built in the TCIS visualization system to allow the spatial and temporal selections of the datasets, the invocation of the tools with user specified parameters, and the display and the delivery of the results. In this presentation, we will describe the key enabling technologies behind the design of the TCIS interactive data portal and analysis tools, including the spatial database technology for the representation and query of the level 2 satellite data, the automatic process flow using web services, the interactive user interface using the Google Earth API, and a common and expandable Python wrapper to invoke the analysis tools.

Multilayer perceptron with local constraint as an emerging method in spatial data analysis

NASA Astrophysics Data System (ADS)

de Bollivier, M.; Dubois, G.; Maignan, M.; Kanevsky, M.

1997-02-01

The use of Geographic Information Systems has revolutionalized the handling and the visualization of geo-referenced data and has underlined the critic role of spatial analysis. The usual tools for such a purpose are geostatistics which are widely used in Earth science. Geostatistics are based upon several hypothesis which are not always verified in practice. On the other hand, Artificial Neural Network (ANN) a priori can be used without special assumptions and are known to be flexible. This paper proposes to discuss the application of ANN in the case of the interpolation of a geo-referenced variable.

Unleashing spatially distributed ecohydrology modeling using Big Data tools

NASA Astrophysics Data System (ADS)

Miles, B.; Idaszak, R.

2015-12-01

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

A new approach in space-time analysis of multivariate hydrological data: Application to Brazil's Nordeste region rainfall

NASA Astrophysics Data System (ADS)

Sicard, Emeline; Sabatier, Robert; Niel, HéLèNe; Cadier, Eric

2002-12-01

The objective of this paper is to implement an original method for spatial and multivariate data, combining a method of three-way array analysis (STATIS) with geostatistical tools. The variables of interest are the monthly amounts of rainfall in the Nordeste region of Brazil, recorded from 1937 to 1975. The principle of the technique is the calculation of a linear combination of the initial variables, containing a large part of the initial variability and taking into account the spatial dependencies. It is a promising method that is able to analyze triple variability: spatial, seasonal, and interannual. In our case, the first component obtained discriminates a group of rain gauges, corresponding approximately to the Agreste, from all the others. The monthly variables of July and August strongly influence this separation. Furthermore, an annual study brings out the stability of the spatial structure of components calculated for each year.

Spatial statistical analysis of tree deaths using airborne digital imagery

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Integrating GIS, cellular automata, and genetic algorithm in urban spatial optimization: a case study of Lanzhou

NASA Astrophysics Data System (ADS)

Xu, Xibao; Zhang, Jianming; Zhou, Xiaojian

2006-10-01

This paper presents a model integrating GIS, cellular automata (CA) and genetic algorithm (GA) in urban spatial optimization. The model involves three objectives of the maximization of land-use efficiency, the maximization of urban spatial harmony and appropriate proportion of each land-use type. CA submodel is designed with standard Moore neighbor and three transition rules to maximize the land-use efficiency and urban spatial harmony, according to the land-use suitability and spatial harmony index. GA submodel is designed with four constraints and seven steps for the maximization of urban spatial harmony and appropriate proportion of each land-use type, including encoding, initializing, calculating fitness, selection, crossover, mutation and elitism. GIS is used to prepare for the input data sets for the model and perform spatial analysis on the results, while CA and GA are integrated to optimize urban spatial structure, programmed with Matlab 7 and coupled with GIS loosely. Lanzhou, a typical valley-basin city with fast urban development, is chosen as the case study. At the end, a detail analysis and evaluation of the spatial optimization with the model are made, and it proves to be a powerful tool in optimizing urban spatial structure and make supplement for urban planning and policy-makers.

Research resource: Update and extension of a glycoprotein hormone receptors web application.

PubMed

Kreuchwig, Annika; Kleinau, Gunnar; Kreuchwig, Franziska; Worth, Catherine L; Krause, Gerd

2011-04-01

The SSFA-GPHR (Sequence-Structure-Function-Analysis of Glycoprotein Hormone Receptors) database provides a comprehensive set of mutation data for the glycoprotein hormone receptors (covering the lutropin, the FSH, and the TSH receptors). Moreover, it provides a platform for comparison and investigation of these homologous receptors and helps in understanding protein malfunctions associated with several diseases. Besides extending the data set (> 1100 mutations), the database has been completely redesigned and several novel features and analysis tools have been added to the web site. These tools allow the focused extraction of semiquantitative mutant data from the GPHR subtypes and different experimental approaches. Functional and structural data of the GPHRs are now linked interactively at the web interface, and new tools for data visualization (on three-dimensional protein structures) are provided. The interpretation of functional findings is supported by receptor morphings simulating intramolecular changes during the activation process, which thus help to trace the potential function of each amino acid and provide clues to the local structural environment, including potentially relocated spatial counterpart residues. Furthermore, double and triple mutations are newly included to allow the analysis of their functional effects related to their spatial interrelationship in structures or homology models. A new important feature is the search option and data visualization by interactive and user-defined snake-plots. These new tools allow fast and easy searches for specific functional data and thereby give deeper insights in the mechanisms of hormone binding, signal transduction, and signaling regulation. The web application "Sequence-Structure-Function-Analysis of GPHRs" is accessible on the internet at http://www.ssfa-gphr.de/.

Spatio-temporal analysis of annual rainfall in Crete, Greece

NASA Astrophysics Data System (ADS)

Varouchakis, Emmanouil A.; Corzo, Gerald A.; Karatzas, George P.; Kotsopoulou, Anastasia

2018-03-01

Analysis of rainfall data from the island of Crete, Greece was performed to identify key hydrological years and return periods as well as to analyze the inter-annual behavior of the rainfall variability during the period 1981-2014. The rainfall spatial distribution was also examined in detail to identify vulnerable areas of the island. Data analysis using statistical tools and spectral analysis were applied to investigate and interpret the temporal course of the available rainfall data set. In addition, spatial analysis techniques were applied and compared to determine the rainfall spatial distribution on the island of Crete. The analysis presented that in contrast to Regional Climate Model estimations, rainfall rates have not decreased, while return periods vary depending on seasonality and geographic location. A small but statistical significant increasing trend was detected in the inter-annual rainfall variations as well as a significant rainfall cycle almost every 8 years. In addition, statistically significant correlation of the island's rainfall variability with the North Atlantic Oscillation is identified for the examined period. On the other hand, regression kriging method combining surface elevation as secondary information improved the estimation of the annual rainfall spatial variability on the island of Crete by 70% compared to ordinary kriging. The rainfall spatial and temporal trends on the island of Crete have variable characteristics that depend on the geographical area and on the hydrological period.

Object classification and outliers analysis in the forthcoming Gaia mission

NASA Astrophysics Data System (ADS)

Ordóñez-Blanco, D.; Arcay, B.; Dafonte, C.; Manteiga, M.; Ulla, A.

2010-12-01

Astrophysics is evolving towards the rational optimization of costly observational material by the intelligent exploitation of large astronomical databases from both terrestrial telescopes and spatial mission archives. However, there has been relatively little advance in the development of highly scalable data exploitation and analysis tools needed to generate the scientific returns from these large and expensively obtained datasets. Among the upcoming projects of astronomical instrumentation, Gaia is the next cornerstone ESA mission. The Gaia survey foresees the creation of a data archive and its future exploitation with automated or semi-automated analysis tools. This work reviews some of the work that is being developed by the Gaia Data Processing and Analysis Consortium for the object classification and analysis of outliers in the forthcoming mission.

Earth-Science Data Co-Locating Tool

NASA Technical Reports Server (NTRS)

Lee, Seungwon; Pan, Lei; Block, Gary L.

2012-01-01

This software is used to locate Earth-science satellite data and climate-model analysis outputs in space and time. This enables the direct comparison of any set of data with different spatial and temporal resolutions. It is written in three separate modules that are clearly separated for their functionality and interface with other modules. This enables a fast development of supporting any new data set. In this updated version of the tool, several new front ends are developed for new products. This software finds co-locatable data pairs for given sets of data products and creates new data products that share the same spatial and temporal coordinates. This facilitates the direct comparison between the two heterogeneous datasets and the comprehensive and synergistic use of the datasets.

'spup' - an R package for uncertainty propagation in spatial environmental modelling

NASA Astrophysics Data System (ADS)

Sawicka, Kasia; Heuvelink, Gerard

2016-04-01

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. Currently, advances in uncertainty propagation 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 (MC) techniques, as well as several uncertainty visualization functions. Uncertain environmental variables are represented in the package as objects whose attribute values may be uncertain and described by probability distributions. Both numerical and categorical data types are handled. Spatial auto-correlation within an attribute and cross-correlation between attributes is also accommodated for. For uncertainty propagation the package has implemented the MC approach with efficient sampling algorithms, i.e. stratified random sampling and Latin hypercube sampling. The design includes facilitation of parallel computing to speed up MC computation. The MC realizations may be used as an input to the environmental models called from R, or externally. Selected static and interactive visualization methods that are understandable by non-experts with limited background in statistics can be used to summarize and visualize uncertainty about the measured input, model parameters and output of the uncertainty propagation. We demonstrate that the 'spup' package is an effective and easy tool to apply and can be used in multi-disciplinary research and model-based decision support.

Spatial Epidemiology of Plasmodium vivax, Afghanistan

PubMed Central

Leslie, Toby; Kolaczinski, Kate; Mohsen, Engineer; Mehboob, Najeebullah; Saleheen, Sarah; Khudonazarov, Juma; Freeman, Tim; Clements, Archie; Rowland, Mark; Kolaczinski, Jan

2006-01-01

Plasmodium vivax is endemic to many areas of Afghanistan. Geographic analysis helped highlight areas of malaria risk and clarified ecologic risk factors for transmission. Remote sensing enabled development of a risk map, thereby providing a valuable tool to help guide malaria control strategies. PMID:17176583

EnviroAtlas Cyanobacteria Assessment Network (CyAN) Dashboard: A Tool for Data Visualization and Exploratory Analysis

EPA Science Inventory

Economic, health, and environmental impacts of cyanobacteria and associated harmful algal blooms are increasingly recognized by policymakers, managers, and scientific researchers. However, spatially-distributed, long-term data on cyanobacteria blooms are largely unavailable. The ...

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

NASA Astrophysics Data System (ADS)

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

2018-03-01

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

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.

qSR: a quantitative super-resolution analysis tool reveals the cell-cycle dependent organization of RNA Polymerase I in live human cells.

PubMed

Andrews, J O; Conway, W; Cho, W -K; Narayanan, A; Spille, J -H; Jayanth, N; Inoue, T; Mullen, S; Thaler, J; Cissé, I I

2018-05-09

We present qSR, an analytical tool for the quantitative analysis of single molecule based super-resolution data. The software is created as an open-source platform integrating multiple algorithms for rigorous spatial and temporal characterizations of protein clusters in super-resolution data of living cells. First, we illustrate qSR using a sample live cell data of RNA Polymerase II (Pol II) as an example of highly dynamic sub-diffractive clusters. Then we utilize qSR to investigate the organization and dynamics of endogenous RNA Polymerase I (Pol I) in live human cells, throughout the cell cycle. Our analysis reveals a previously uncharacterized transient clustering of Pol I. Both stable and transient populations of Pol I clusters co-exist in individual living cells, and their relative fraction vary during cell cycle, in a manner correlating with global gene expression. Thus, qSR serves to facilitate the study of protein organization and dynamics with very high spatial and temporal resolutions directly in live cell.

Spatio-temporal analysis of small-area intestinal parasites infections in Ghana.

PubMed

Osei, F B; Stein, A

2017-09-22

Intestinal parasites infection is a major public health burden in low and middle-income countries. In Ghana, it is amongst the top five morbidities. In order to optimize scarce resources, reliable information on its geographical distribution is needed to guide periodic mass drug administration to populations of high risk. We analyzed district level morbidities of intestinal parasites between 2010 and 2014 using exploratory spatial analysis and geostatistics. We found a significantly positive Moran's Index of spatial autocorrelation for each year, suggesting that adjoining districts have similar risk levels. Using local Moran's Index, we found high-high clusters extending towards the Guinea and Sudan Savannah ecological zones, whereas low-low clusters extended within the semi-deciduous forest and transitional ecological zones. Variograms indicated that local and regional scale risk factors modulate the variation of intestinal parasites. Poisson kriging maps showed smoothed spatially varied distribution of intestinal parasites risk. These emphasize the need for a follow-up investigation into the exact determining factors modulating the observed patterns. The findings also underscored the potential of exploratory spatial analysis and geostatistics as tools for visualizing the spatial distribution of small area intestinal worms infections.

Quantitative analysis of biological tissues using Fourier transform-second-harmonic generation imaging

NASA Astrophysics Data System (ADS)

Ambekar Ramachandra Rao, Raghu; Mehta, Monal R.; Toussaint, Kimani C., Jr.

2010-02-01

We demonstrate the use of Fourier transform-second-harmonic generation (FT-SHG) imaging of collagen fibers as a means of performing quantitative analysis of obtained images of selected spatial regions in porcine trachea, ear, and cornea. Two quantitative markers, preferred orientation and maximum spatial frequency are proposed for differentiating structural information between various spatial regions of interest in the specimens. The ear shows consistent maximum spatial frequency and orientation as also observed in its real-space image. However, there are observable changes in the orientation and minimum feature size of fibers in the trachea indicating a more random organization. Finally, the analysis is applied to a 3D image stack of the cornea. It is shown that the standard deviation of the orientation is sensitive to the randomness in fiber orientation. Regions with variations in the maximum spatial frequency, but with relatively constant orientation, suggest that maximum spatial frequency is useful as an independent quantitative marker. We emphasize that FT-SHG is a simple, yet powerful, tool for extracting information from images that is not obvious in real space. This technique can be used as a quantitative biomarker to assess the structure of collagen fibers that may change due to damage from disease or physical injury.

Coastal Online Analysis and Synthesis Tool 2.0 (COAST)

NASA Technical Reports Server (NTRS)

Brown, Richard B.; Navard, Andrew R.; Nguyen, Beth T.

2009-01-01

The Coastal Online Assessment and Synthesis Tool (COAST) 3D geobrowser has been developed to integrate disparate coastal datasets from NASA and other sources into a desktop tool that provides new data visualization and analysis capabilities for coastal researchers, managers, and residents. It is built upon the widely used NASA-developed open source World Wind geobrowser from NASA Ames (Patrick Hogan et al.) .Net and C# version is used for development. It is leveraged off of World Wind community shared code samples and COAST 2.0 enhancement direction is based on Coastal science community feedback and needs assessment (GOMA). The main objective is to empower the user to bring more user-meaningful data into multi-layered, multi-temporal spatial context.

Computation of the spectrum of spatial Lyapunov exponents for the spatially extended beam-plasma systems and electron-wave devices

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

Hramov, Alexander E.; Saratov State Technical University, Politechnicheskaja str., 77, Saratov 410054; Koronovskii, Alexey A.

2012-08-15

The spectrum of Lyapunov exponents is powerful tool for the analysis of the complex system dynamics. In the general framework of nonlinear dynamics, a number of the numerical techniques have been developed to obtain the spectrum of Lyapunov exponents for the complex temporal behavior of the systems with a few degree of freedom. Unfortunately, these methods cannot be applied directly to analysis of complex spatio-temporal dynamics of plasma devices which are characterized by the infinite phase space, since they are the spatially extended active media. In the present paper, we propose the method for the calculation of the spectrum ofmore » the spatial Lyapunov exponents (SLEs) for the spatially extended beam-plasma systems. The calculation technique is applied to the analysis of chaotic spatio-temporal oscillations in three different beam-plasma model: (1) simple plasma Pierce diode, (2) coupled Pierce diodes, and (3) electron-wave system with backward electromagnetic wave. We find an excellent agreement between the system dynamics and the behavior of the spectrum of the spatial Lyapunov exponents. Along with the proposed method, the possible problems of SLEs calculation are also discussed. It is shown that for the wide class of the spatially extended systems, the set of quantities included in the system state for SLEs calculation can be reduced using the appropriate feature of the plasma systems.« less

Visualization tool for human-machine interface designers

NASA Astrophysics Data System (ADS)

Prevost, Michael P.; Banda, Carolyn P.

1991-06-01

As modern human-machine systems continue to grow in capabilities and complexity, system operators are faced with integrating and managing increased quantities of information. Since many information components are highly related to each other, optimizing the spatial and temporal aspects of presenting information to the operator has become a formidable task for the human-machine interface (HMI) designer. The authors describe a tool in an early stage of development, the Information Source Layout Editor (ISLE). This tool is to be used for information presentation design and analysis; it uses human factors guidelines to assist the HMI designer in the spatial layout of the information required by machine operators to perform their tasks effectively. These human factors guidelines address such areas as the functional and physical relatedness of information sources. By representing these relationships with metaphors such as spring tension, attractors, and repellers, the tool can help designers visualize the complex constraint space and interacting effects of moving displays to various alternate locations. The tool contains techniques for visualizing the relative 'goodness' of a configuration, as well as mechanisms such as optimization vectors to provide guidance toward a more optimal design. Also available is a rule-based design checker to determine compliance with selected human factors guidelines.

Toward automatic finite element analysis

NASA Technical Reports Server (NTRS)

Kela, Ajay; Perucchio, Renato; Voelcker, Herbert

1987-01-01

Two problems must be solved if the finite element method is to become a reliable and affordable blackbox engineering tool. Finite element meshes must be generated automatically from computer aided design databases and mesh analysis must be made self-adaptive. The experimental system described solves both problems in 2-D through spatial and analytical substructuring techniques that are now being extended into 3-D.

An analysis of spatial and socio-economic determinants of tuberculosis in Hermosillo, Mexico, 2000-2006.

PubMed

Alvarez-Hernández, G; Lara-Valencia, F; Reyes-Castro, P A; Rascón-Pacheco, R A

2010-06-01

The city of Hermosillo, in Northwest Mexico, has a higher incidence of tuberculosis (TB) than the national average. However, the intra-urban TB distribution, which could limit the effectiveness of preventive strategies and control, is unknown. Using geographic information systems (GIS) and spatial analysis, we characterized the geographical distribution of TB by basic geostatistical area (BGA), and compared it with a social deprivation index. Univariate and bivariate techniques were used to detect risk areas. Globally, TB in the city of Hermosillo is not spatially auto-correlated, but local clusters with high incidence and mortality rates were identified in the northwest, central-east and southwest sections of the city. BGAs with high social deprivation had an excess risk of TB. GIS and spatial analysis are useful tools to detect high TB risk areas in the city of Hermosillo. Such areas may be vulnerable due to low socio-economic status. The study of small geographical areas in urban settings similar to Hermosillo could indicate the best course of action to be taken for TB prevention and control.

CWDPRNP: A tool for cervid prion sequence analysis in program R

USGS Publications Warehouse

Miller, William L.; Walter, W. David

2017-01-01

Chronic wasting disease is a fatal, neurological disease caused by an infectious prion protein, which affects economically and ecologically important members of the family Cervidae. Single nucleotide polymorphisms within the prion protein gene have been linked to differential susceptibility to the disease in many species. Wildlife managers are seeking to determine the frequencies of disease-associated alleles and genotypes and delineate spatial genetic patterns. The CWDPRNP package, implemented in program R, provides a unified framework for analyzing prion protein gene variability and spatial structure.

Atlas-Guided Segmentation of Vervet Monkey Brain MRI

PubMed Central

Fedorov, Andriy; Li, Xiaoxing; Pohl, Kilian M; Bouix, Sylvain; Styner, Martin; Addicott, Merideth; Wyatt, Chris; Daunais, James B; Wells, William M; Kikinis, Ron

2011-01-01

The vervet monkey is an important nonhuman primate model that allows the study of isolated environmental factors in a controlled environment. Analysis of monkey MRI often suffers from lower quality images compared with human MRI because clinical equipment is typically used to image the smaller monkey brain and higher spatial resolution is required. This, together with the anatomical differences of the monkey brains, complicates the use of neuroimage analysis pipelines tuned for human MRI analysis. In this paper we developed an open source image analysis framework based on the tools available within the 3D Slicer software to support a biological study that investigates the effect of chronic ethanol exposure on brain morphometry in a longitudinally followed population of male vervets. We first developed a computerized atlas of vervet monkey brain MRI, which was used to encode the typical appearance of the individual brain structures in MRI and their spatial distribution. The atlas was then used as a spatial prior during automatic segmentation to process two longitudinal scans per subject. Our evaluation confirms the consistency and reliability of the automatic segmentation. The comparison of atlas construction strategies reveals that the use of a population-specific atlas leads to improved accuracy of the segmentation for subcortical brain structures. The contribution of this work is twofold. First, we describe an image processing workflow specifically tuned towards the analysis of vervet MRI that consists solely of the open source software tools. Second, we develop a digital atlas of vervet monkey brain MRIs to enable similar studies that rely on the vervet model. PMID:22253661

Current Research in Land Use Impact Assessment

EPA Science Inventory

There is a continuing debate on how to best evaluate land use impacts within the LCA framework. While this problem is spatially and temporally complex, recent advances in tool development are providing options to allow a GIS-based analysis of various ecosystem services given the...

This is like that, only bigger and messier

USDA-ARS?s Scientific Manuscript database

Cluster analysis is a core tool of vegetation science; we have always wanted to divide a complex world into manageable chunks. In vegetation science, we classify both vegetation and sites. Both have clear management applications. Various types of spatial classifications are used to delineate agroec...

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

DOE PAGES

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.; ...

2016-02-05

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

Multimodality hard-x-ray imaging of a chromosome with nanoscale spatial resolution

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

Yan, Hanfei; Nazaretski, Evgeny; Lauer, Kenneth R.

Here, we developed a scanning hard x-ray microscope using a new class of x-ray nano-focusing optic called a multilayer Laue lens and imaged a chromosome with nanoscale spatial resolution. The combination of the hard x-ray's superior penetration power, high sensitivity to elemental composition, high spatial-resolution and quantitative analysis creates a unique tool with capabilities that other microscopy techniques cannot provide. Using this microscope, we simultaneously obtained absorption-, phase-, and fluorescence-contrast images of Pt-stained human chromosome samples. The high spatial-resolution of the microscope and its multi-modality imaging capabilities enabled us to observe the internal ultra-structures of a thick chromosome without sectioningmore » it.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Gis-Based Spatial Statistical Analysis of College Graduates Employment

NASA Astrophysics Data System (ADS)

Tang, R.

2012-07-01

It is urgently necessary to be aware of the distribution and employment status of college graduates for proper allocation of human resources and overall arrangement of strategic industry. This study provides empirical evidence regarding the use of geocoding and spatial analysis in distribution and employment status of college graduates based on the data from 2004-2008 Wuhan Municipal Human Resources and Social Security Bureau, China. Spatio-temporal distribution of employment unit were analyzed with geocoding using ArcGIS software, and the stepwise multiple linear regression method via SPSS software was used to predict the employment and to identify spatially associated enterprise and professionals demand in the future. The results show that the enterprises in Wuhan east lake high and new technology development zone increased dramatically from 2004 to 2008, and tended to distributed southeastward. Furthermore, the models built by statistical analysis suggest that the specialty of graduates major in has an important impact on the number of the employment and the number of graduates engaging in pillar industries. In conclusion, the combination of GIS and statistical analysis which helps to simulate the spatial distribution of the employment status is a potential tool for human resource development research.

Click-On-Diagram Questions: a New Tool to Study Conceptions Using Classroom Response Systems

NASA Astrophysics Data System (ADS)

LaDue, Nicole D.; Shipley, Thomas F.

2018-06-01

Geoscience instructors depend upon photos, diagrams, and other visualizations to depict geologic structures and processes that occur over a wide range of temporal and spatial scales. This proof-of-concept study tests click-on-diagram (COD) questions, administered using a classroom response system (CRS), as a research tool for identifying spatial misconceptions. First, we propose a categorization of spatial conceptions associated with geoscience concepts. Second, we implemented the COD questions in an undergraduate introductory geology course. Each question was implemented three times: pre-instruction, post-instruction, and at the end of the course to evaluate the stability of students' conceptual understanding. We classified each instance as (1) a false belief that was easily remediated, (2) a flawed mental model that was not fully transformed, or (3) a robust misconception that persisted despite targeted instruction. Geographic Information System (GIS) software facilitated spatial analysis of students' answers. The COD data confirmed known misconceptions about Earth's structure, geologic time, and base level and revealed a novel robust misconception about hot spot formation. Questions with complex spatial attributes were less likely to change following instruction and more likely to be classified as a robust misconception. COD questions provided efficient access to students' conceptual understanding. CRS-administered COD questions present an opportunity to gather spatial conceptions with large groups of students, immediately, building the knowledge base about students' misconceptions and providing feedback to guide instruction.

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

NASA Astrophysics Data System (ADS)

Langhammer, Jakub; Lendzioch, Theodora; Mirijovsky, Jakub

2016-04-01

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

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

Geospatial Technologies and Higher Education in Argentina

ERIC Educational Resources Information Center

Leguizamon, Saturnino

2010-01-01

The term "geospatial technologies" encompasses a large area of fields involving cartography, spatial analysis, geographic information system, remote sensing, global positioning systems and many others. These technologies should be expected to be available (as "natural tools") for a country with a large surface and a variety of…

INTEGRATING LANDSCAPE AND HYDROLOGIC ANALYSIS FOR WATERSHED ASSESSMENT IN AN AMERICAN SEMI-ARID BIOREGION

EPA Science Inventory

The objective of this study is to demonstrate the application of operational hydrologic modeling and landscape assessment tools to investigate the temporal and spatial effects of varying levels of anthropogenic disturbance in a semi-arid catchment and examine the consequences of ...

NIRS-SPM: statistical parametric mapping for near infrared spectroscopy

NASA Astrophysics Data System (ADS)

Tak, Sungho; Jang, Kwang Eun; Jung, Jinwook; Jang, Jaeduck; Jeong, Yong; Ye, Jong Chul

2008-02-01

Even though there exists a powerful statistical parametric mapping (SPM) tool for fMRI, similar public domain tools are not available for near infrared spectroscopy (NIRS). In this paper, we describe a new public domain statistical toolbox called NIRS-SPM for quantitative analysis of NIRS signals. Specifically, NIRS-SPM statistically analyzes the NIRS data using GLM and makes inference as the excursion probability which comes from the random field that are interpolated from the sparse measurement. In order to obtain correct inference, NIRS-SPM offers the pre-coloring and pre-whitening method for temporal correlation estimation. For simultaneous recording NIRS signal with fMRI, the spatial mapping between fMRI image and real coordinate in 3-D digitizer is estimated using Horn's algorithm. These powerful tools allows us the super-resolution localization of the brain activation which is not possible using the conventional NIRS analysis tools.

Multi Criteria Evaluation Module for RiskChanges Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Olyazadeh, Roya; Jaboyedoff, Michel; van Westen, Cees; Bakker, Wim

2015-04-01

Multi-Criteria Evaluation (MCE) module is one of the five modules of RiskChanges spatial decision support system. RiskChanges web-based platform aims to analyze changes in hydro-meteorological risk and provides tools for selecting the best risk reduction alternative. It is developed under CHANGES framework (changes-itn.eu) and INCREO project (increo-fp7.eu). MCE tool helps decision makers and spatial planners to evaluate, sort and rank the decision alternatives. The users can choose among different indicators that are defined within the system using Risk and Cost Benefit analysis results besides they can add their own indicators. Subsequently the system standardizes and prioritizes them. Finally, the best decision alternative is selected by using the weighted sum model (WSM). The Application of this work is to facilitate the effect of MCE for analyzing changing risk over the time under different scenarios and future years by adopting a group decision making into practice and comparing the results by numeric and graphical view within the system. We believe that this study helps decision-makers to achieve the best solution by expressing their preferences for strategies under future scenarios. Keywords: Multi-Criteria Evaluation, Spatial Decision Support System, Weighted Sum Model, Natural Hazard Risk Management

A fast and robust bulk-loading algorithm for indexing very large digital elevation datasets II. Experimental results

NASA Astrophysics Data System (ADS)

Rodríguez, Félix R.; Barrena, Manuel

2011-07-01

The spatial indexing of eventually all the available topographic information of Earth is a highly valuable tool for different geoscientific application domains. The Shuttle Radar Topography Mission (SRTM) collected and made available to the public one of the world's largest digital elevation models (DEMs). With the aim of providing on easier and faster access to these data by improving their further analysis and processing, we have indexed the SRTM DEM by means of a spatial index based on the kd-tree data structure, called the Q-tree. This paper is the second in a two-part series that includes a thorough performance analysis to validate the bulk-load algorithm efficiency of the Q-tree. We investigate performance measuring elapsed time in different contexts, analyzing disk space usage, testing response time with typical queries, and validating the final index structure balance. In addition, the paper includes performance comparisons with Oracle 11g that helps to understand the real cost of our proposal. Our tests prove that the proposed algorithm outperforms Oracle 11g using around a 9% of the elapsed time, taking six times less storage with more than 96% of page utilization, and getting faster response times to spatial queries issued on 4.5 million points. In addition to this, the behavior of the spatial index has been successfully tested on both an open GIS (VT Builder) and a visualizer tool derived from the previous one.

COSMO-SkyMed and GIS applications

NASA Astrophysics Data System (ADS)

Milillo, Pietro; Sole, Aurelia; Serio, Carmine

2013-04-01

Geographic Information Systems (GIS) and Remote Sensing have become key technology tools for the collection, storage and analysis of spatially referenced data. Industries that utilise these spatial technologies include agriculture, forestry, mining, market research as well as the environmental analysis . Synthetic Aperture Radar (SAR) is a coherent active sensor operating in the microwave band which exploits relative motion between antenna and target in order to obtain a finer spatial resolution in the flight direction exploiting the Doppler effect. SAR have wide applications in Remote Sensing such as cartography, surface deformation detection, forest cover mapping, urban planning, disasters monitoring , surveillance etc… The utilization of satellite remote sensing and GIS technology for this applications has proven to be a powerful and effective tool for environmental monitoring. Remote sensing techniques are often less costly and time-consuming for large geographic areas compared to conventional methods, moreover GIS technology provides a flexible environment for, analyzing and displaying digital data from various sources necessary for classification, change detection and database development. The aim of this work si to illustrate the potential of COSMO-SkyMed data and SAR applications in a GIS environment, in particular a demostration of the operational use of COSMO-SkyMed SAR data and GIS in real cases will be provided for what concern DEM validation, river basin estimation, flood mapping and landslide monitoring.

A Modular GIS-Based Software Architecture for Model Parameter Estimation using the Method of Anchored Distributions (MAD)

NASA Astrophysics Data System (ADS)

Ames, D. P.; Osorio-Murillo, C.; Over, M. W.; Rubin, Y.

2012-12-01

The Method of Anchored Distributions (MAD) is an inverse modeling technique that is well-suited for estimation of spatially varying parameter fields using limited observations and Bayesian methods. This presentation will discuss the design, development, and testing of a free software implementation of the MAD technique using the open source DotSpatial geographic information system (GIS) framework, R statistical software, and the MODFLOW groundwater model. This new tool, dubbed MAD-GIS, is built using a modular architecture that supports the integration of external analytical tools and models for key computational processes including a forward model (e.g. MODFLOW, HYDRUS) and geostatistical analysis (e.g. R, GSLIB). The GIS-based graphical user interface provides a relatively simple way for new users of the technique to prepare the spatial domain, to identify observation and anchor points, to perform the MAD analysis using a selected forward model, and to view results. MAD-GIS uses the Managed Extensibility Framework (MEF) provided by the Microsoft .NET programming platform to support integration of different modeling and analytical tools at run-time through a custom "driver." Each driver establishes a connection with external programs through a programming interface, which provides the elements for communicating with core MAD software. This presentation gives an example of adapting the MODFLOW to serve as the external forward model in MAD-GIS for inferring the distribution functions of key MODFLOW parameters. Additional drivers for other models are being developed and it is expected that the open source nature of the project will engender the development of additional model drivers by 3rd party scientists.

Multisite-multivariable sensitivity analysis of distributed watershed models: enhancing the perceptions from computationally frugal methods

USDA-ARS?s Scientific Manuscript database

This paper assesses the impact of different likelihood functions in identifying sensitive parameters of the highly parameterized, spatially distributed Soil and Water Assessment Tool (SWAT) watershed model for multiple variables at multiple sites. The global one-factor-at-a-time (OAT) method of Morr...

Spatial allocation of forest recreation value

Treesearch

Kenneth A. Baerenklau; Armando Gonzalez-Caban; Catrina Paez; Edgard Chavez

2009-01-01

Non-market valuation methods and geographic information systems are useful planning and management tools for public land managers. Recent attention has been given to investigation and demonstration of methods for combining these tools to provide spatially-explicit representations of non-market value. Most of these efforts have focused on spatial allocation of...

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

NASA Astrophysics Data System (ADS)

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

2015-07-01

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

The Uncertainties on the GIS Based Land Suitability Assessment for Urban and Rural Planning

NASA Astrophysics Data System (ADS)

Liu, H.; Zhan, Q.; Zhan, M.

2017-09-01

The majority of the research on the uncertainties of spatial data and spatial analysis focuses on some specific data feature or analysis tool. Few have accomplished the uncertainties of the whole process of an application like planning, making the research of uncertainties detached from practical applications. The paper discusses the uncertainties of the geographical information systems (GIS) based land suitability assessment in planning on the basis of literature review. The uncertainties considered range from index system establishment to the classification of the final result. Methods to reduce the uncertainties arise from the discretization of continuous raster data and the index weight determination are summarized. The paper analyzes the merits and demerits of the "Nature Breaks" method which is broadly used by planners. It also explores the other factors which impact the accuracy of the final classification like the selection of class numbers, intervals and the autocorrelation of the spatial data. In the conclusion part, the paper indicates that the adoption of machine learning methods should be modified to integrate the complexity of land suitability assessment. The work contributes to the application of spatial data and spatial analysis uncertainty research on land suitability assessment, and promotes the scientific level of the later planning and decision-making.

Integrating Spatial Land Use Analysis and Mathematical Material Flow Analysis for Nutrient Management: A Case Study of the Bang Pakong River Basin in Thailand

NASA Astrophysics Data System (ADS)

Kupkanchanakul, Wallapa; Kwonpongsagoon, Suphaphat; Bader, Hans-Peter; Scheidegger, Ruth

2015-05-01

Rivers in developing and emerging countries often lack good water quality. Tools to assess the water quality in rivers, including identification of possible sources of pollution, are therefore of increasing importance. The aim of this study is to apply mathematical material flow and spatial land use analyses to identify and geographically locate the main nitrogen and phosphorus sources and processes in Bang Pakong Basin (BPB). Potential measures to mitigate the nitrogen and phosphorus loads to the water system can then be efficiently evaluated. The combination of these two methods reveals the overall nutrient load as well as local "hot spots." This allows possible mitigation measures to be discussed with regard to their spatial location. This approach goes beyond previous work in which mathematical material flow analysis was shown to be a useful tool to investigate sources of nutrients regardless of their location. The results show that the main sources contributing nutrients to waterways are aquaculture, such as shrimp, tilapia, catfish, and sea bass farming, as well as rice paddies along the main river. Additional sources contributing nutrients to this basin are field crops, livestock, aquaculture, households, and industry. High levels of nutrient inflows come from feeds and fertilizers through aquaculture and rice cultivation. The excess nutrients run into the waterways by direct discharge from aquaculture and runoff processes from rice paddies. Scenario analysis shows that management practices for aquaculture, rice, pig, and poultry farming are key drivers for reducing nutrients in the BPB.

Integrating spatial land use analysis and mathematical material flow analysis for nutrient management: a case study of the Bang Pakong River Basin in Thailand.

PubMed

Kupkanchanakul, Wallapa; Kwonpongsagoon, Suphaphat; Bader, Hans-Peter; Scheidegger, Ruth

2015-05-01

Rivers in developing and emerging countries often lack good water quality. Tools to assess the water quality in rivers, including identification of possible sources of pollution, are therefore of increasing importance. The aim of this study is to apply mathematical material flow and spatial land use analyses to identify and geographically locate the main nitrogen and phosphorus sources and processes in Bang Pakong Basin (BPB). Potential measures to mitigate the nitrogen and phosphorus loads to the water system can then be efficiently evaluated. The combination of these two methods reveals the overall nutrient load as well as local "hot spots." This allows possible mitigation measures to be discussed with regard to their spatial location. This approach goes beyond previous work in which mathematical material flow analysis was shown to be a useful tool to investigate sources of nutrients regardless of their location. The results show that the main sources contributing nutrients to waterways are aquaculture, such as shrimp, tilapia, catfish, and sea bass farming, as well as rice paddies along the main river. Additional sources contributing nutrients to this basin are field crops, livestock, aquaculture, households, and industry. High levels of nutrient inflows come from feeds and fertilizers through aquaculture and rice cultivation. The excess nutrients run into the waterways by direct discharge from aquaculture and runoff processes from rice paddies. Scenario analysis shows that management practices for aquaculture, rice, pig, and poultry farming are key drivers for reducing nutrients in the BPB.

Analysis of post-mining excavations as places for municipal waste

NASA Astrophysics Data System (ADS)

Górniak-Zimroz, Justyna

2018-01-01

Waste management planning is an interdisciplinary task covering a wide range of issues including costs, legal requirements, spatial planning, environmental protection, geography, demographics, and techniques used in collecting, transporting, processing and disposing of waste. Designing and analyzing this issue is difficult and requires the use of advanced analysis methods and tools available in GIS geographic information systems containing readily available graphical and descriptive databases, data analysis tools providing expert decision support while selecting the best-designed alternative, and simulation models that allow the user to simulate many variants of waste management together with graphical visualization of the results of performed analyzes. As part of the research study, there have been works undertaken concerning the use of multi-criteria data analysis in waste management in areas located in southwestern Poland. These works have proposed the inclusion in waste management of post-mining excavations as places for the final or temporary collection of waste assessed in terms of their suitability with the tools available in GIS systems.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Application of Serological Tools and Spatial Analysis to Investigate Malaria Transmission Dynamics in Highland Areas of Southwest Uganda

PubMed Central

Lynch, Caroline A.; Cook, Jackie; Nanyunja, Sarah; Bruce, Jane; Bhasin, Amit; Drakeley, Chris; Roper, Cally; Pearce, Richard; Rwakimari, John B.; Abeku, Tarekegn A.; Corran, Patrick; Cox, Jonathan

2016-01-01

Serological markers, combined with spatial analysis, offer a comparatively more sensitive means by which to measure and detect foci of malaria transmission in highland areas than traditional malariometric indicators. Plasmodium falciparum parasite prevalence, seroprevalence, and seroconversion rate to P. falciparum merozoite surface protein-119 (MSP-119) were measured in a cross-sectional survey to determine differences in transmission between altitudinal strata. Clusters of P. falciparum parasite prevalence and high antibody responses to MSP-119 were detected and compared. Results show that P. falciparum prevalence and seroprevalence generally decreased with increasing altitude. However, transmission was heterogeneous with hotspots of prevalence and/or seroprevalence detected in both highland and highland fringe altitudes, including a serological hotspot at 2,200 m. Results demonstrate that seroprevalence can be used as an additional tool to identify hotspots of malaria transmission that might be difficult to detect using traditional cross-sectional parasite surveys or through vector studies. Our study findings identify ways in which malaria prevention and control can be more effectively targeted in highland or low transmission areas via serological measures. These tools will become increasingly important for countries with an elimination agenda and/or where malaria transmission is becoming patchy and focal, but receptivity to malaria transmission remains high. PMID:27022156

Measuring changes in chemistry, composition, and molecular structure within hair fibers by infrared and Raman spectroscopic imaging.

PubMed

Zhang, Guojin; Senak, Laurence; Moore, David J

2011-05-01

Spatially resolved infrared (IR) and Raman images are acquired from human hair cross sections or intact hair fibers. The full informational content of these spectra are spatially correlated to hair chemistry, anatomy, and structural organization through univariate and multivariate data analysis. Specific IR and Raman images from untreated human hair describing the spatial dependence of lipid and protein distribution, protein secondary structure, lipid chain conformational order, and distribution of disulfide cross-links in hair protein are presented in this study. Factor analysis of the image plane acquired with IR microscopy in hair sections, permits delineation of specific micro-regions within the hair. These data indicate that both IR and Raman imaging of molecular structural changes in a specific region of hair will prove to be valuable tools in the understanding of hair structure, physiology, and the effect of various stresses upon its integrity.

Remote Sensing in Geography in the New Millennium: Prospects, Challenges, and Opportunities

NASA Technical Reports Server (NTRS)

Quattrochi, Dale A.; Jensen, John R.; Morain, Stanley A.; Walsh, Stephen J.; Ridd, Merrill K.

1999-01-01

Remote sensing science contributes greatly to our understanding of the Earth's ecosystems and cultural landscapes. Almost all the natural and social sciences, including geography, rely heavily on remote sensing to provide quantitative, and indispensable spatial information. Many geographers have made significant contributions to remote sensing science since the 1970s, including the specification of advanced remote sensing systems, improvements in analog and digital image analysis, biophysical modeling, and terrain analysis. In fact, the Remote Sensing Specialty Group (RSSG) is one of the largest specialty groups within the AAG with over 500 members. Remote sensing in concert with a geographic information systems, offers much value to geography as both an incisive spatial-analytical tool and as a scholarly pursuit that adds to the body of geographic knowledge on the whole. The "power" of remote sensing as a research endeavor in geography lies in its capabilities for obtaining synoptic, near-real time data at many spatial and temporal scales, and in many regions of the electromagnetic spectrum - from microwave, to RADAR, to visible, and reflective and thermal infrared. In turn, these data present a vast compendium of information for assessing Earth attributes and characte6stics that are at the very core of geography. Here we revisit how remote sensing has become a fundamental and important tool for geographical research, and how with the advent of new and improved sensing systems to be launched in the near future, remote sensing will further advance geographical analysis in the approaching New Millennium.

Spatial correlation of auroral zone geomagnetic variations

NASA Astrophysics Data System (ADS)

Jackel, B. J.; Davalos, A.

2016-12-01

Magnetic field perturbations in the auroral zone are produced by a combination of distant ionospheric and local ground induced currents. Spatial and temporal structure of these currents is scientifically interesting and can also have a significant influence on critical infrastructure.Ground-based magnetometer networks are an essential tool for studying these phenomena, with the existing complement of instruments in Canada providing extended local time coverage. In this study we examine the spatial correlation between magnetic field observations over a range of scale lengths. Principal component and canonical correlation analysis are used to quantify relationships between multiple sites. Results could be used to optimize network configurations, validate computational models, and improve methods for empirical interpolation.

Measurement of in situ sulfur isotopes by laser ablation multi-collector ICPMS: opening Pandora’s Box

USGS Publications Warehouse

Ridley, William I.; Pribil, Michael; Koenig, Alan E.; Slack, John F.

2015-01-01

Laser ablation multi-collector ICPMS is a modern tool for in situ measurement of S isotopes. Advantages of the technique are speed of analysis and relatively minor matrix effects combined with spatial resolution sufficient for many applications. The main disadvantage is a more destructive sampling mechanism relative to the ion microprobe technique. Recent advances in instrumentation allow precise measurement with spatial resolutions down to 25 microns. We describe specific examples from economic geology where increased spatial resolution has greatly expanded insights into the sources and evolution of fluids that cause mineralization and illuminated genetic relations between individual deposits in single mineral districts.

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain.

PubMed

Dominkovics, Pau; Granell, Carlos; Pérez-Navarro, Antoni; Casals, Martí; Orcau, Angels; Caylà, Joan A

2011-11-29

Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios.

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

PubMed Central

2013-01-01

Background Fine-scale and longitudinal geospatial analysis of health risks in challenging urban areas is often limited by the lack of other spatial layers even if case data are available. Underlying population counts, residential context, and associated causative factors such as standing water or trash locations are often missing unless collected through logistically difficult, and often expensive, surveys. The lack of spatial context also hinders the interpretation of results and designing intervention strategies structured around analytical insights. This paper offers a ubiquitous spatial data collection approach using a spatial video that can be used to improve analysis and involve participatory collaborations. A case study will be used to illustrate this approach with three health risks mapped at the street scale for a coastal community in Haiti. Methods Spatial video was used to collect street and building scale information, including standing water, trash accumulation, presence of dogs, cohort specific population characteristics, and other cultural phenomena. These data were digitized into Google Earth and then coded and analyzed in a GIS using kernel density and spatial filtering approaches. The concentrations of these risks around area schools which are sometimes sources of diarrheal disease infection because of the high concentration of children and variable sanitary practices will show the utility of the method. In addition schools offer potential locations for cholera education interventions. Results Previously unavailable fine scale health risk data vary in concentration across the town, with some schools being proximate to greater concentrations of the mapped risks. The spatial video is also used to validate coded data and location specific risks within these “hotspots”. Conclusions Spatial video is a tool that can be used in any environment to improve local area health analysis and intervention. The process is rapid and can be repeated in study sites through time to track spatio-temporal dynamics of the communities. Its simplicity should also be used to encourage local participatory collaborations. PMID:23587358

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

PubMed

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

2013-04-15

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

Development of spatial density maps based on geoprocessing web services: application to tuberculosis incidence in Barcelona, Spain

PubMed Central

2011-01-01

Background Health professionals and authorities strive to cope with heterogeneous data, services, and statistical models to support decision making on public health. Sophisticated analysis and distributed processing capabilities over geocoded epidemiological data are seen as driving factors to speed up control and decision making in these health risk situations. In this context, recent Web technologies and standards-based web services deployed on geospatial information infrastructures have rapidly become an efficient way to access, share, process, and visualize geocoded health-related information. Methods Data used on this study is based on Tuberculosis (TB) cases registered in Barcelona city during 2009. Residential addresses are geocoded and loaded into a spatial database that acts as a backend database. The web-based application architecture and geoprocessing web services are designed according to the Representational State Transfer (REST) principles. These web processing services produce spatial density maps against the backend database. Results The results are focused on the use of the proposed web-based application to the analysis of TB cases in Barcelona. The application produces spatial density maps to ease the monitoring and decision making process by health professionals. We also include a discussion of how spatial density maps may be useful for health practitioners in such contexts. Conclusions In this paper, we developed web-based client application and a set of geoprocessing web services to support specific health-spatial requirements. Spatial density maps of TB incidence were generated to help health professionals in analysis and decision-making tasks. The combined use of geographic information tools, map viewers, and geoprocessing services leads to interesting possibilities in handling health data in a spatial manner. In particular, the use of spatial density maps has been effective to identify the most affected areas and its spatial impact. This study is an attempt to demonstrate how web processing services together with web-based mapping capabilities suit the needs of health practitioners in epidemiological analysis scenarios. PMID:22126392

Spectral Properties and Dynamics of Gold Nanorods Revealed by EMCCD Based Spectral-Phasor Method

PubMed Central

Chen, Hongtao; Digman, Michelle A.

2015-01-01

Gold nanorods (NRs) with tunable plasmon-resonant absorption in the near-infrared region have considerable advantages over organic fluorophores as imaging agents. However, the luminescence spectral properties of NRs have not been fully explored at the single particle level in bulk due to lack of proper analytic tools. Here we present a global spectral phasor analysis method which allows investigations of NRs' spectra at single particle level with their statistic behavior and spatial information during imaging. The wide phasor distribution obtained by the spectral phasor analysis indicates spectra of NRs are different from particle to particle. NRs with different spectra can be identified graphically in corresponding spatial images with high spectral resolution. Furthermore, spectral behaviors of NRs under different imaging conditions, e.g. different excitation powers and wavelengths, were carefully examined by our laser-scanning multiphoton microscope with spectral imaging capability. Our results prove that the spectral phasor method is an easy and efficient tool in hyper-spectral imaging analysis to unravel subtle changes of the emission spectrum. Moreover, we applied this method to study the spectral dynamics of NRs during direct optical trapping and by optothermal trapping. Interestingly, spectral shifts were observed in both trapping phenomena. PMID:25684346

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

CDMetaPOP: An individual-based, eco-evolutionary model for spatially explicit simulation of landscape demogenetics

USGS Publications Warehouse

Landguth, Erin L; Bearlin, Andrew; Day, Casey; Dunham, Jason B.

2016-01-01

1. Combining landscape demographic and genetics models offers powerful methods for addressing questions for eco-evolutionary applications.2. Using two illustrative examples, we present Cost–Distance Meta-POPulation, a program to simulate changes in neutral and/or selection-driven genotypes through time as a function of individual-based movement, complex spatial population dynamics, and multiple and changing landscape drivers.3. Cost–Distance Meta-POPulation provides a novel tool for questions in landscape genetics by incorporating population viability analysis, while linking directly to conservation applications.

Design and implementation of visualization methods for the CHANGES Spatial Decision Support System

NASA Astrophysics Data System (ADS)

Cristal, Irina; van Westen, Cees; Bakker, Wim; Greiving, Stefan

2014-05-01

The CHANGES Spatial Decision Support System (SDSS) is a web-based system aimed for risk assessment and the evaluation of optimal risk reduction alternatives at local level as a decision support tool in long-term natural risk management. The SDSS use multidimensional information, integrating thematic, spatial, temporal and documentary data. The role of visualization in this context becomes of vital importance for efficiently representing each dimension. This multidimensional aspect of the required for the system risk information, combined with the diversity of the end-users imposes the use of sophisticated visualization methods and tools. The key goal of the present work is to exploit efficiently the large amount of data in relation to the needs of the end-user, utilizing proper visualization techniques. Three main tasks have been accomplished for this purpose: categorization of the end-users, the definition of system's modules and the data definition. The graphical representation of the data and the visualization tools were designed to be relevant to the data type and the purpose of the analysis. Depending on the end-users category, each user should have access to different modules of the system and thus, to the proper visualization environment. The technologies used for the development of the visualization component combine the latest and most innovative open source JavaScript frameworks, such as OpenLayers 2.13.1, ExtJS 4 and GeoExt 2. Moreover, the model-view-controller (MVC) pattern is used in order to ensure flexibility of the system at the implementation level. Using the above technologies, the visualization techniques implemented so far offer interactive map navigation, querying and comparison tools. The map comparison tools are of great importance within the SDSS and include the following: swiping tool for comparison of different data of the same location; raster subtraction for comparison of the same phenomena varying in time; linked views for comparison of data from different locations and a time slider tool for monitoring changes in spatio-temporal data. All these techniques are part of the interactive interface of the system and make use of spatial and spatio-temporal data. Further significant aspects of the visualization component include conventional cartographic techniques and visualization of non-spatial data. The main expectation from the present work is to offer efficient visualization of risk-related data in order to facilitate the decision making process, which is the final purpose of the CHANGES SDSS. This work is part of the "CHANGES" project, funded by the European Community's 7th Framework Programme.

Situational Awareness Geospatial Application (iSAGA)

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

Sher, Benjamin

Situational Awareness Geospatial Application (iSAGA) is a geospatial situational awareness software tool that uses an algorithm to extract location data from nearly any internet-based, or custom data source and display it geospatially; allows user-friendly conduct of spatial analysis using custom-developed tools; searches complex Geographic Information System (GIS) databases and accesses high resolution imagery. iSAGA has application at the federal, state and local levels of emergency response, consequence management, law enforcement, emergency operations and other decision makers as a tool to provide complete, visual, situational awareness using data feeds and tools selected by the individual agency or organization. Feeds may bemore » layered and custom tools developed to uniquely suit each subscribing agency or organization. iSAGA may similarly be applied to international agencies and organizations.« less

Virtual Technologies to Develop Visual-Spatial Ability in Engineering Students

ERIC Educational Resources Information Center

Roca-González, Cristina; Martin-Gutierrez, Jorge; García-Dominguez, Melchor; Carrodeguas, Mª del Carmen Mato

2017-01-01

The present study assessed a short training experiment to improve spatial abilities using two tools based on virtual technologies: one focused on manipulation of specific geometric virtual pieces, and the other consisting of virtual orienteering game. The two tools can help improve spatial abilities required for many engineering problem-solving…

Integration of modern statistical tools for the analysis of climate extremes into the web-GIS “CLIMATE”

NASA Astrophysics Data System (ADS)

Ryazanova, A. A.; Okladnikov, I. G.; Gordov, E. P.

2017-11-01

The frequency of occurrence and magnitude of precipitation and temperature extreme events show positive trends in several geographical regions. These events must be analyzed and studied in order to better understand their impact on the environment, predict their occurrences, and mitigate their effects. For this purpose, we augmented web-GIS called “CLIMATE” to include a dedicated statistical package developed in the R language. The web-GIS “CLIMATE” is a software platform for cloud storage processing and visualization of distributed archives of spatial datasets. It is based on a combined use of web and GIS technologies with reliable procedures for searching, extracting, processing, and visualizing the spatial data archives. The system provides a set of thematic online tools for the complex analysis of current and future climate changes and their effects on the environment. The package includes new powerful methods of time-dependent statistics of extremes, quantile regression and copula approach for the detailed analysis of various climate extreme events. Specifically, the very promising copula approach allows obtaining the structural connections between the extremes and the various environmental characteristics. The new statistical methods integrated into the web-GIS “CLIMATE” can significantly facilitate and accelerate the complex analysis of climate extremes using only a desktop PC connected to the Internet.

An implicit higher-order spatially accurate scheme for solving time dependent flows on unstructured meshes

NASA Astrophysics Data System (ADS)

Tomaro, Robert F.

1998-07-01

The present research is aimed at developing a higher-order, spatially accurate scheme for both steady and unsteady flow simulations using unstructured meshes. The resulting scheme must work on a variety of general problems to ensure the creation of a flexible, reliable and accurate aerodynamic analysis tool. To calculate the flow around complex configurations, unstructured grids and the associated flow solvers have been developed. Efficient simulations require the minimum use of computer memory and computational times. Unstructured flow solvers typically require more computer memory than a structured flow solver due to the indirect addressing of the cells. The approach taken in the present research was to modify an existing three-dimensional unstructured flow solver to first decrease the computational time required for a solution and then to increase the spatial accuracy. The terms required to simulate flow involving non-stationary grids were also implemented. First, an implicit solution algorithm was implemented to replace the existing explicit procedure. Several test cases, including internal and external, inviscid and viscous, two-dimensional, three-dimensional and axi-symmetric problems, were simulated for comparison between the explicit and implicit solution procedures. The increased efficiency and robustness of modified code due to the implicit algorithm was demonstrated. Two unsteady test cases, a plunging airfoil and a wing undergoing bending and torsion, were simulated using the implicit algorithm modified to include the terms required for a moving and/or deforming grid. Secondly, a higher than second-order spatially accurate scheme was developed and implemented into the baseline code. Third- and fourth-order spatially accurate schemes were implemented and tested. The original dissipation was modified to include higher-order terms and modified near shock waves to limit pre- and post-shock oscillations. The unsteady cases were repeated using the higher-order spatially accurate code. The new solutions were compared with those obtained using the second-order spatially accurate scheme. Finally, the increased efficiency of using an implicit solution algorithm in a production Computational Fluid Dynamics flow solver was demonstrated for steady and unsteady flows. A third- and fourth-order spatially accurate scheme has been implemented creating a basis for a state-of-the-art aerodynamic analysis tool.

Integration of vegetation community spatial data into a prescribed fire planning process at Shenandoah National Park, Virginia (USA)

USGS Publications Warehouse

Young, John A.; Mahan, Carolyn G.; Forder, Melissa

2017-01-01

Many eastern forest communities depend on fire for regeneration or are enhanced by fire as a restoration practice. However, the use of prescribed fire in the mesic forested environments and the densely populated regions of the eastern United States has been limited. The objective of our research was to develop a science-based approach to prioritizing the use of prescribed fire in appropriate forest types in the eastern United States based on a set of desired management outcomes. Through a process of expert elicitation and data analysis, we assessed and integrated recent vegetation community mapping results along with other available spatial data layers into a spatial prioritization tool for prescribed fire planning at Shenandoah National Park (Virginia, USA). The integration of vegetation spatial data allowed for development of per-pixel priority rankings and exclusion areas enabling precise targeting of fire management activities on the ground, as well as a park-wide ranking of fire planning compartments. We demonstrate the use and evaluation of this approach through implementation and monitoring of a prescribed burn and show that progress is being made toward desired conditions. Integration of spatial data into the fire planning process has served as a collaborative tool for the implementation of prescribed fire projects, which assures projects will be planned in the most appropriate areas to meet objectives that are supported by current science.

J-Earth: An Essential Resource for Terrestrial Remote Sensing and Data Analysis

NASA Astrophysics Data System (ADS)

Dunn, S.; Rupp, J.; Cheeseman, S.; Christensen, P. R.; Prashad, L. C.; Dickenshied, S.; Anwar, S.; Noss, D.; Murray, K.

2011-12-01

There is a need for a software tool that has the ability to display and analyze various types of earth science and social data through a simple, user-friendly interface. The J-Earth software tool has been designed to be easily accessible for download and intuitive use, regardless of the technical background of the user base. This tool does not require courses or text books to learn to use, yet is powerful enough to allow a more general community of users to perform complex data analysis. Professions that will benefit from this tool range from geologists, geographers, and climatologists to sociologists, economists, and ecologists as well as policy makers. J-Earth was developed by the Arizona State University Mars Space Flight Facility as part of the JMARS (Java Mission-planning and Analysis for Remote Sensing) suite of open-source tools. The program is a Geographic Information Systems (GIS) application used for viewing and processing satellite and airborne remote sensing data. While the functionality of JMARS has historically focused on the research needs of the planetary science community, J-Earth has been designed for a much broader Earth-based user audience. NASA instrument products accessible within J-Earth include data from ASTER, GOES, Landsat, MODIS, and TIMS. While J-Earth contains exceptionally comprehensive and high resolution satellite-derived data and imagery, this tool also includes many socioeconomic data products from projects lead by international organizations and universities. Datasets used in J-Earth take the form of grids, rasters, remote sensor "stamps", maps, and shapefiles. Some highly demanded global datasets available within J-Earth include five levels of administrative/political boundaries, climate data for current conditions as well as models for future climates, population counts and densities, land cover/land use, and poverty indicators. While this application does share the same powerful functionality of JMARS, J-Earth's apperance is enhanced for much easier data analysis. J-Earth utilizes a layering system to view data from different sources which can then be exported, scaled, colored and superimposed for quick comparisons. Users may now perform spatial analysis over several diverse datasets with respect to a defined geographic area or the entire globe. In addition, several newly acquired global datasets contain a temporal dimension which when accessed through J-Earth, make this a unique and powerful tool for spatial analysis over time. The functionality and ease of use set J-Earth apart from all other terrestrial GIS software packages and enable endless social, political, and scientific possibilities

Spatial Representations in Older Adults are Not Modified by Action: Evidence from Tool Use

PubMed Central

Costello, Matthew C.; Bloesch, Emily K.; Davoli, Christopher C.; Panting, Nicholas D.; Abrams, Richard A.; Brockmole, James R.

2015-01-01

Theories of embodied perception hold that the visual system is calibrated by both the body schema and the action system, allowing for adaptive action-perception responses. One example of embodied perception involves the effects of tool-use on distance perception, in which wielding a tool with the intention to act upon a target appears to bring that object closer. This tool-based spatial compression (i.e., tool-use effect) has been studied exclusively with younger adults, but it is unknown whether the phenomenon exists with older adults. In this study, we examined the effects of tool use on distance perception in younger and older adults in two experiments. In Experiment 1, younger and older adults estimated the distances of targets just beyond peripersonal space while either wielding a tool or pointing with the hand. Younger adults, but not older adults, estimated targets to be closer after reaching with a tool. In Experiment 2, younger and older adults estimated the distance to remote targets while using either a baton or laser pointer. Younger adults displayed spatial compression with the laser pointer compared to the baton, although older adults did not. Taken together, these findings indicate a generalized absence of the tool-use effect in older adults during distance estimation suggesting that the visuomotor system of older adults does not remap from peripersonal to extrapersonal spatial representations during tool use. PMID:26052886

Open source tools for fluorescent imaging.

PubMed

Hamilton, Nicholas A

2012-01-01

As microscopy becomes increasingly automated and imaging expands in the spatial and time dimensions, quantitative analysis tools for fluorescent imaging are becoming critical to remove both bottlenecks in throughput as well as fully extract and exploit the information contained in the imaging. In recent years there has been a flurry of activity in the development of bio-image analysis tools and methods with the result that there are now many high-quality, well-documented, and well-supported open source bio-image analysis projects with large user bases that cover essentially every aspect from image capture to publication. These open source solutions are now providing a viable alternative to commercial solutions. More importantly, they are forming an interoperable and interconnected network of tools that allow data and analysis methods to be shared between many of the major projects. Just as researchers build on, transmit, and verify knowledge through publication, open source analysis methods and software are creating a foundation that can be built upon, transmitted, and verified. Here we describe many of the major projects, their capabilities, and features. We also give an overview of the current state of open source software for fluorescent microscopy analysis and the many reasons to use and develop open source methods. Copyright © 2012 Elsevier Inc. All rights reserved.

Spatial photosensitizer fluorescence emission predictive analysis for photodynamic therapy monitoring applied to a skin disease

NASA Astrophysics Data System (ADS)

Salas-García, Irene; Fanjul-Vélez, Félix; Arce-Diego, José Luis

2012-03-01

The development of Photodynamic Therapy (PDT) predictive models has become a valuable tool for an optimal treatment planning, monitoring and dosimetry adjustment. A few attempts have achieved a quite complete characterization of the complex photochemical and photophysical processes involved, even taking into account superficial fluorescence in the target tissue. The present work is devoted to the application of a predictive PDT model to obtain fluorescence tomography information during PDT when applied to a skin disease. The model takes into account the optical radiation distribution, a non-homogeneous topical photosensitizer distribution, the time dependent photochemical interaction and the photosensitizer fluorescence emission. The results show the spatial evolution of the photosensitizer fluorescence emission and the amount of singlet oxygen produced during PDT. The depth dependent photosensitizer fluorescence emission obtained is essential to estimate the spatial photosensitizer concentration and its degradation due to photobleaching. As a consequence the proposed approach could be used to predict the photosensitizer fluorescence tomographic measurements during PDT. The singlet oxygen prediction could also be employed as a valuable tool to predict the short term treatment outcome.

Profiles of Motor Laterality in Young Athletes' Performance of Complex Movements: Merging the MOTORLAT and PATHoops Tools

PubMed Central

Castañer, Marta; Andueza, Juan; Hileno, Raúl; Puigarnau, Silvia; Prat, Queralt; Camerino, Oleguer

2018-01-01

Laterality is a key aspect of the analysis of basic and specific motor skills. It is relevant to sports because it involves motor laterality profiles beyond left-right preference and spatial orientation of the body. The aim of this study was to obtain the laterality profiles of young athletes, taking into account the synergies between the support and precision functions of limbs and body parts in the performance of complex motor skills. We applied two instruments: (a) MOTORLAT, a motor laterality inventory comprising 30 items of basic, specific, and combined motor skills, and (b) the Precision and Agility Tapping over Hoops (PATHoops) task, in which participants had to perform a path by stepping in each of 14 hoops arranged on the floor, allowing the observation of their feet, left-right preference and spatial orientation. A total of 96 young athletes performed the PATHoops task and the 30 MOTORLAT items, allowing us to obtain data about limb dominance and spatial orientation of the body in the performance of complex motor skills. Laterality profiles were obtained by means of a cluster analysis and a correlational analysis and a contingency analysis were applied between the motor skills and spatial orientation actions performed. The results obtained using MOTORLAT show that the combined motor skills criterion (for example, turning while jumping) differentiates athletes' uses of laterality, showing a clear tendency toward mixed laterality profiles in the performance of complex movements. In the PATHoops task, the best spatial orientation strategy was “same way” (same foot and spatial wing) followed by “opposite way” (opposite foot and spatial wing), in keeping with the research assumption that actions unfolding in a horizontal direction in front of an observer's eyes are common in a variety of sports. PMID:29930527

GISpark: A Geospatial Distributed Computing Platform for Spatiotemporal Big Data

NASA Astrophysics Data System (ADS)

Wang, S.; Zhong, E.; Wang, E.; Zhong, Y.; Cai, W.; Li, S.; Gao, S.

2016-12-01

Geospatial data are growing exponentially because of the proliferation of cost effective and ubiquitous positioning technologies such as global remote-sensing satellites and location-based devices. Analyzing large amounts of geospatial data can provide great value for both industrial and scientific applications. Data- and compute- intensive characteristics inherent in geospatial big data increasingly pose great challenges to technologies of data storing, computing and analyzing. Such challenges require a scalable and efficient architecture that can store, query, analyze, and visualize large-scale spatiotemporal data. Therefore, we developed GISpark - a geospatial distributed computing platform for processing large-scale vector, raster and stream data. GISpark is constructed based on the latest virtualized computing infrastructures and distributed computing architecture. OpenStack and Docker are used to build multi-user hosting cloud computing infrastructure for GISpark. The virtual storage systems such as HDFS, Ceph, MongoDB are combined and adopted for spatiotemporal data storage management. Spark-based algorithm framework is developed for efficient parallel computing. Within this framework, SuperMap GIScript and various open-source GIS libraries can be integrated into GISpark. GISpark can also integrated with scientific computing environment (e.g., Anaconda), interactive computing web applications (e.g., Jupyter notebook), and machine learning tools (e.g., TensorFlow/Orange). The associated geospatial facilities of GISpark in conjunction with the scientific computing environment, exploratory spatial data analysis tools, temporal data management and analysis systems make up a powerful geospatial computing tool. GISpark not only provides spatiotemporal big data processing capacity in the geospatial field, but also provides spatiotemporal computational model and advanced geospatial visualization tools that deals with other domains related with spatial property. We tested the performance of the platform based on taxi trajectory analysis. Results suggested that GISpark achieves excellent run time performance in spatiotemporal big data applications.

Integrating 3D Visualization and GIS in Planning Education

ERIC Educational Resources Information Center

Yin, Li

2010-01-01

Most GIS-related planning practices and education are currently limited to two-dimensional mapping and analysis although 3D GIS is a powerful tool to study the complex urban environment in its full spatial extent. This paper reviews current GIS and 3D visualization uses and development in planning practice and education. Current literature…

Full Life Cycle of Data Analysis with Climate Model Diagnostic Analyzer (CMDA)

NASA Astrophysics Data System (ADS)

Lee, S.; Zhai, C.; Pan, L.; Tang, B.; Zhang, J.; Bao, Q.; Malarout, N.

2017-12-01

We have developed a system that supports the full life cycle of a data analysis process, from data discovery, to data customization, to analysis, to reanalysis, to publication, and to reproduction. The system called Climate Model Diagnostic Analyzer (CMDA) is designed to demonstrate that the full life cycle of data analysis can be supported within one integrated system for climate model diagnostic evaluation with global observational and reanalysis datasets. CMDA has four subsystems that are highly integrated to support the analysis life cycle. Data System manages datasets used by CMDA analysis tools, Analysis System manages CMDA analysis tools which are all web services, Provenance System manages the meta data of CMDA datasets and the provenance of CMDA analysis history, and Recommendation System extracts knowledge from CMDA usage history and recommends datasets/analysis tools to users. These four subsystems are not only highly integrated but also easily expandable. New datasets can be easily added to Data System and scanned to be visible to the other subsystems. New analysis tools can be easily registered to be available in the Analysis System and Provenance System. With CMDA, a user can start a data analysis process by discovering datasets of relevance to their research topic using the Recommendation System. Next, the user can customize the discovered datasets for their scientific use (e.g. anomaly calculation, regridding, etc) with tools in the Analysis System. Next, the user can do their analysis with the tools (e.g. conditional sampling, time averaging, spatial averaging) in the Analysis System. Next, the user can reanalyze the datasets based on the previously stored analysis provenance in the Provenance System. Further, they can publish their analysis process and result to the Provenance System to share with other users. Finally, any user can reproduce the published analysis process and results. By supporting the full life cycle of climate data analysis, CMDA improves the research productivity and collaboration level of its user.

Modeling Criminal Activity in Urban Landscapes

NASA Astrophysics Data System (ADS)

Brantingham, Patricia; Glässer, Uwe; Jackson, Piper; Vajihollahi, Mona

Computational and mathematical methods arguably have an enormous potential for serving practical needs in crime analysis and prevention by offering novel tools for crime investigations and experimental platforms for evidence-based policy making. We present a comprehensive formal framework and tool support for mathematical and computational modeling of criminal behavior to facilitate systematic experimental studies of a wide range of criminal activities in urban environments. The focus is on spatial and temporal aspects of different forms of crime, including opportunistic and serial violent crimes. However, the proposed framework provides a basis to push beyond conventional empirical research and engage the use of computational thinking and social simulations in the analysis of terrorism and counter-terrorism.

Correlated Raman micro-spectroscopy and scanning electron microscopy analyses of flame retardants in environmental samples: a micro-analytical tool for probing chemical composition, origin and spatial distribution.

PubMed

Ghosal, Sutapa; Wagner, Jeff

2013-07-07

We present correlated application of two micro-analytical techniques: scanning electron microscopy/energy dispersive X-ray spectroscopy (SEM/EDS) and Raman micro-spectroscopy (RMS) for the non-invasive characterization and molecular identification of flame retardants (FRs) in environmental dusts and consumer products. The SEM/EDS-RMS technique offers correlated, morphological, molecular, spatial distribution and semi-quantitative elemental concentration information at the individual particle level with micrometer spatial resolution and minimal sample preparation. The presented methodology uses SEM/EDS analyses for rapid detection of particles containing FR specific elements as potential indicators of FR presence in a sample followed by correlated RMS analyses of the same particles for characterization of the FR sub-regions and surrounding matrices. The spatially resolved characterization enabled by this approach provides insights into the distributional heterogeneity as well as potential transfer and exposure mechanisms for FRs in the environment that is typically not available through traditional FR analysis. We have used this methodology to reveal a heterogeneous distribution of highly concentrated deca-BDE particles in environmental dust, sometimes in association with identifiable consumer materials. The observed coexistence of deca-BDE with consumer material in dust is strongly indicative of its release into the environment via weathering/abrasion of consumer products. Ingestion of such enriched FR particles in dust represents a potential for instantaneous exposure to high FR concentrations. Therefore, correlated SEM/RMS analysis offers a novel investigative tool for addressing an area of important environmental concern.

Spatial Harmonic Decomposition as a tool for unsteady flow phenomena analysis

NASA Astrophysics Data System (ADS)

Duparchy, A.; Guillozet, J.; De Colombel, T.; Bornard, L.

2014-03-01

Hydropower is already the largest single renewable electricity source today but its further development will face new deployment constraints such as large-scale projects in emerging economies and the growth of intermittent renewable energy technologies. The potential role of hydropower as a grid stabilizer leads to operating hydro power plants in "off-design" zones. As a result, new methods of analyzing associated unsteady phenomena are needed to improve the design of hydraulic turbines. The key idea of the development is to compute a spatial description of a phenomenon by using a combination from several sensor signals. The spatial harmonic decomposition (SHD) extends the concept of so-called synchronous and asynchronous pulsations by projecting sensor signals on a linearly independent set of a modal scheme. This mathematical approach is very generic as it can be applied on any linear distribution of a scalar quantity defined on a closed curve. After a mathematical description of SHD, this paper will discuss the impact of instrumentation and provide tools to understand SHD signals. Then, as an example of a practical application, SHD is applied on a model test measurement in order to capture and describe dynamic pressure fields. Particularly, the spatial description of the phenomena provides new tools to separate the part of pressure fluctuations that contribute to output power instability or mechanical stresses. The study of the machine stability in partial load operating range in turbine mode or the comparison between the gap pressure field and radial thrust behavior during turbine brake operation are both relevant illustrations of SHD contribution.

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

DOE PAGES

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

2016-10-02

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

Stackfile Database

NASA Technical Reports Server (NTRS)

deVarvalho, Robert; Desai, Shailen D.; Haines, Bruce J.; Kruizinga, Gerhard L.; Gilmer, Christopher

2013-01-01

This software provides storage retrieval and analysis functionality for managing satellite altimetry data. It improves the efficiency and analysis capabilities of existing database software with improved flexibility and documentation. It offers flexibility in the type of data that can be stored. There is efficient retrieval either across the spatial domain or the time domain. Built-in analysis tools are provided for frequently performed altimetry tasks. This software package is used for storing and manipulating satellite measurement data. It was developed with a focus on handling the requirements of repeat-track altimetry missions such as Topex and Jason. It was, however, designed to work with a wide variety of satellite measurement data [e.g., Gravity Recovery And Climate Experiment -- GRACE). The software consists of several command-line tools for importing, retrieving, and analyzing satellite measurement data.

Integrated analysis of remote sensing products from basic geological surveys. [Brazil

NASA Technical Reports Server (NTRS)

Dasilvafagundesfilho, E. (Principal Investigator)

1984-01-01

Recent advances in remote sensing led to the development of several techniques to obtain image information. These techniques as effective tools in geological maping are analyzed. A strategy for optimizing the images in basic geological surveying is presented. It embraces as integrated analysis of spatial, spectral, and temporal data through photoptic (color additive viewer) and computer processing at different scales, allowing large areas survey in a fast, precise, and low cost manner.

Erosion Risks in Selected Watersheds for the 2005 School Fire Located Near Pomeroy, Washington on Predominately Ash-Cap Soils

Treesearch

William Elliot; Ina Sue Miller; Brandon Glaza

2007-01-01

A limited erosion potential analysis was carried out on the 50,000 acre School Fire. Three WEPP interfaces were used for the analysis, a GIS wizard, an online interface and a windows interface. Ten watersheds within the fire area were modeled with the GeoWEPP tool (a geo-spatial interface for WEPP, Water Erosion Predication Project). The watersheds covered 18,823 acres...

Prospects of photonic nanojets for precise exposure on microobjects

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

Geints, Yu. E., E-mail: ygeints@iao.ru; Zuev Institute of Atmospheric Optics, SB Russian Academy of Sciences, Acad. Zuev Square 1, Tomsk, 634021; Panina, E. K., E-mail: pek@iao.ru

We report on the new optical tool for precise manipulation of various microobjects. This tool is referred to as a “photonic nanojet” (PJ) and corresponds to specific spatially localized and high-intensity area formed near micron-sized transparent spherical dielectric particles illuminated by a visible laser radiation The descriptive analysis of the morphological shapes of photonic nanojets is presented. The PJ shape characterization is based on the numerical calculations of the near-field distribution according to the Mie theory and accounts for jet dimensions and shape complexity.

Estimation of spatial-temporal gait parameters using a low-cost ultrasonic motion analysis system.

PubMed

Qi, Yongbin; Soh, Cheong Boon; Gunawan, Erry; Low, Kay-Soon; Thomas, Rijil

2014-08-20

In this paper, a low-cost motion analysis system using a wireless ultrasonic sensor network is proposed and investigated. A methodology has been developed to extract spatial-temporal gait parameters including stride length, stride duration, stride velocity, stride cadence, and stride symmetry from 3D foot displacements estimated by the combination of spherical positioning technique and unscented Kalman filter. The performance of this system is validated against a camera-based system in the laboratory with 10 healthy volunteers. Numerical results show the feasibility of the proposed system with average error of 2.7% for all the estimated gait parameters. The influence of walking speed on the measurement accuracy of proposed system is also evaluated. Statistical analysis demonstrates its capability of being used as a gait assessment tool for some medical applications.

Implementing a Global Tool for Mercy Corps Based on Spatially Continuous Precipitation Analysis for Resiliency Monitoring and Measuring at the Community-Scale

NASA Astrophysics Data System (ADS)

Tomlin, J. N.; El-Behaedi, R.; McCartney, S.; Lingo, R.; Thieme, A.

2017-12-01

Global water resources are important for societies, economies, and the environment. In Niger, limited water resources restrict the expansion of agriculture and communities. Mercy Corps currently works in over 40 countries around the world to address a variety of stresses which include water resources and building long-term food resilience. As Mercy Corps seeks to integrate the use of Earth observations, NASA has established a partnership to help facilitate this effort incorporating Tropical Rainfall Measuring Mission (TRMM), Global Precipitation Measurement (GPM), and Climate Hazards Group InfraRed Precipitation with Station (CHIRPS) data to create a standardized precipitation index that highlights low and high rainfall from 1981 - 2016. The team created a Google Earth Engine tool that combines precipitation data with other metrics of stress in Niger. The system is designed to be able to incorporate groundwater storage data as it becomes available. This tool allows for near real-time updates of trends in precipitation and improves Mercy Corps' ability to spatially evaluate changes in resiliency by monitoring shocks and stressors.

Applying spatial analysis tools in public health: an example using SaTScan to detect geographic targets for colorectal cancer screening interventions.

PubMed

Sherman, Recinda L; Henry, Kevin A; Tannenbaum, Stacey L; Feaster, Daniel J; Kobetz, Erin; Lee, David J

2014-03-20

Epidemiologists are gradually incorporating spatial analysis into health-related research as geocoded cases of disease become widely available and health-focused geospatial computer applications are developed. One health-focused application of spatial analysis is cluster detection. Using cluster detection to identify geographic areas with high-risk populations and then screening those populations for disease can improve cancer control. SaTScan is a free cluster-detection software application used by epidemiologists around the world to describe spatial clusters of infectious and chronic disease, as well as disease vectors and risk factors. The objectives of this article are to describe how spatial analysis can be used in cancer control to detect geographic areas in need of colorectal cancer screening intervention, identify issues commonly encountered by SaTScan users, detail how to select the appropriate methods for using SaTScan, and explain how method selection can affect results. As an example, we used various methods to detect areas in Florida where the population is at high risk for late-stage diagnosis of colorectal cancer. We found that much of our analysis was underpowered and that no single method detected all clusters of statistical or public health significance. However, all methods detected 1 area as high risk; this area is potentially a priority area for a screening intervention. Cluster detection can be incorporated into routine public health operations, but the challenge is to identify areas in which the burden of disease can be alleviated through public health intervention. Reliance on SaTScan's default settings does not always produce pertinent results.

Difet: Distributed Feature Extraction Tool for High Spatial Resolution Remote Sensing Images

NASA Astrophysics Data System (ADS)

Eken, S.; Aydın, E.; Sayar, A.

2017-11-01

In this paper, we propose distributed feature extraction tool from high spatial resolution remote sensing images. Tool is based on Apache Hadoop framework and Hadoop Image Processing Interface. Two corner detection (Harris and Shi-Tomasi) algorithms and five feature descriptors (SIFT, SURF, FAST, BRIEF, and ORB) are considered. Robustness of the tool in the task of feature extraction from LandSat-8 imageries are evaluated in terms of horizontal scalability.

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.

Bayesian learning for spatial filtering in an EEG-based brain-computer interface.

PubMed

Zhang, Haihong; Yang, Huijuan; Guan, Cuntai

2013-07-01

Spatial filtering for EEG feature extraction and classification is an important tool in brain-computer interface. However, there is generally no established theory that links spatial filtering directly to Bayes classification error. To address this issue, this paper proposes and studies a Bayesian analysis theory for spatial filtering in relation to Bayes error. Following the maximum entropy principle, we introduce a gamma probability model for describing single-trial EEG power features. We then formulate and analyze the theoretical relationship between Bayes classification error and the so-called Rayleigh quotient, which is a function of spatial filters and basically measures the ratio in power features between two classes. This paper also reports our extensive study that examines the theory and its use in classification, using three publicly available EEG data sets and state-of-the-art spatial filtering techniques and various classifiers. Specifically, we validate the positive relationship between Bayes error and Rayleigh quotient in real EEG power features. Finally, we demonstrate that the Bayes error can be practically reduced by applying a new spatial filter with lower Rayleigh quotient.

PRANAS: A New Platform for Retinal Analysis and Simulation.

PubMed

Cessac, Bruno; Kornprobst, Pierre; Kraria, Selim; Nasser, Hassan; Pamplona, Daniela; Portelli, Geoffrey; Viéville, Thierry

2017-01-01

The retina encodes visual scenes by trains of action potentials that are sent to the brain via the optic nerve. In this paper, we describe a new free access user-end software allowing to better understand this coding. It is called PRANAS (https://pranas.inria.fr), standing for Platform for Retinal ANalysis And Simulation. PRANAS targets neuroscientists and modelers by providing a unique set of retina-related tools. PRANAS integrates a retina simulator allowing large scale simulations while keeping a strong biological plausibility and a toolbox for the analysis of spike train population statistics. The statistical method (entropy maximization under constraints) takes into account both spatial and temporal correlations as constraints, allowing to analyze the effects of memory on statistics. PRANAS also integrates a tool computing and representing in 3D (time-space) receptive fields. All these tools are accessible through a friendly graphical user interface. The most CPU-costly of them have been implemented to run in parallel.

Mass Spectrometry Imaging for the Investigation of Intratumor Heterogeneity.

PubMed

Balluff, B; Hanselmann, M; Heeren, R M A

2017-01-01

One of the big clinical challenges in the treatment of cancer is the different behavior of cancer patients under guideline therapy. An important determinant for this phenomenon has been identified as inter- and intratumor heterogeneity. While intertumor heterogeneity refers to the differences in cancer characteristics between patients, intratumor heterogeneity refers to the clonal and nongenetic molecular diversity within a patient. The deciphering of intratumor heterogeneity is recognized as key to the development of novel therapeutics or treatment regimens. The investigation of intratumor heterogeneity is challenging since it requires an untargeted molecular analysis technique that accounts for the spatial and temporal dynamics of the tumor. So far, next-generation sequencing has contributed most to the understanding of clonal evolution within a cancer patient. However, it falls short in accounting for the spatial dimension. Mass spectrometry imaging (MSI) is a powerful tool for the untargeted but spatially resolved molecular analysis of biological tissues such as solid tumors. As it provides multidimensional datasets by the parallel acquisition of hundreds of mass channels, multivariate data analysis methods can be applied for the automated annotation of tissues. Moreover, it integrates the histology of the sample, which enables studying the molecular information in a histopathological context. This chapter will illustrate how MSI in combination with statistical methods and histology has been used for the description and discovery of intratumor heterogeneity in different cancers. This will give evidence that MSI constitutes a unique tool for the investigation of intratumor heterogeneity, and could hence become a key technology in cancer research. © 2017 Elsevier Inc. All rights reserved.

Hydrologic analysis for selection and placement of conservation practices at the watershed scale

NASA Astrophysics Data System (ADS)

Wilson, C.; Brooks, E. S.; Boll, J.

2012-12-01

When a water body is exceeding water quality standards and a Total Maximum Daily Load has been established, conservation practices in the watershed are able to reduce point and non-point source pollution. Hydrological analysis is needed to place conservation practices in the most hydrologically sensitive areas. The selection and placement of conservation practices, however, is challenging in ungauged watersheds with little or no data for the hydrological analysis. The objective of this research is to perform a hydrological analysis for mitigation of erosion and total phosphorus in a mixed land use watershed, and to select and place the conservation practices in the most sensitive areas. The study area is the Hangman Creek watershed in Idaho and Washington State, upstream of Long Lake (WA) reservoir, east of Spokane, WA. While the pollutant of concern is total phosphorus (TP), reductions in TP were translated to total suspended solids or reductions in nonpoint source erosion and sediment delivery to streams. Hydrological characterization was done with a simple web-based tool, which runs the Water Erosion Prediction Project (WEPP) model for representative land types in the watersheds, where a land type is defined as a unique combination of soil type, slope configuration, land use and management, and climate. The web-based tool used site-specific spatial and temporal data on land use, soil physical parameters, slope, and climate derived from readily available data sources and provided information on potential pollutant pathways (i.e. erosion, runoff, lateral flow, and percolation). Multiple land types representative in the watershed were ordered from most effective to least effective, and displayed spatially using GIS. The methodology for the Hangman Creek watershed was validated in the nearby Paradise Creek watershed that has long-term stream discharge and monitoring as well as land use data. Output from the web-based tool shows the potential reductions for different tillage practices, buffer strips, streamside management, and conversion to the conservation reserve program in the watershed. The output also includes the relationship between land area where conservation practices are placed and the potential reduction in pollution, showing the diminished returns on investment as less sensitive areas are being treated. This application of a simple web-based tool and the use of a physically-based erosion model (i.e. WEPP) illustrates that quantitative, spatial and temporal analysis of changes in pollutant loading and site-specific recommendations of conservation practices can be made in ungauged watersheds.

A spatial scan statistic for survival data based on Weibull distribution.

PubMed

Bhatt, Vijaya; Tiwari, Neeraj

2014-05-20

The spatial scan statistic has been developed as a geographical cluster detection analysis tool for different types of data sets such as Bernoulli, Poisson, ordinal, normal and exponential. We propose a scan statistic for survival data based on Weibull distribution. It may also be used for other survival distributions, such as exponential, gamma, and log normal. The proposed method is applied on the survival data of tuberculosis patients for the years 2004-2005 in Nainital district of Uttarakhand, India. Simulation studies reveal that the proposed method performs well for different survival distribution functions. Copyright © 2013 John Wiley & Sons, Ltd.

Spectrum of classes of point emitters of electromagnetic wave fields.

PubMed

Castañeda, Román

2016-09-01

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

An optimized method to calculate error correction capability of tool influence function in frequency domain

NASA Astrophysics Data System (ADS)

Wang, Jia; Hou, Xi; Wan, Yongjian; Shi, Chunyan

2017-10-01

An optimized method to calculate error correction capability of tool influence function (TIF) in certain polishing conditions will be proposed based on smoothing spectral function. The basic mathematical model for this method will be established in theory. A set of polishing experimental data with rigid conformal tool is used to validate the optimized method. The calculated results can quantitatively indicate error correction capability of TIF for different spatial frequency errors in certain polishing conditions. The comparative analysis with previous method shows that the optimized method is simpler in form and can get the same accuracy results with less calculating time in contrast to previous method.

A New Tool for Climatic Analysis Using the Koppen Climate Classification

ERIC Educational Resources Information Center

Larson, Paul R.; Lohrengel, C. Frederick, II

2011-01-01

The purpose of climate classification is to help make order of the seemingly endless spatial distribution of climates. The Koppen classification system in a modified format is the most widely applied system in use today. This system may not be the best nor most complete climate classification that can be conceived, but it has gained widespread…

Designing a Structured and Interactive Learning Environment Based on GIS for Secondary Geography Education

ERIC Educational Resources Information Center

Liu, Suxia; Zhu, Xuan

2008-01-01

Geographic information systems (GIS) are computer-based tools for geographic data analysis and spatial visualization. They have become one of the information and communications technologies for education at all levels. This article reviews the current status of GIS in schools, analyzes the requirements of a GIS-based learning environment from…

Simulation of anisoplanatic imaging through optical turbulence using numerical wave propagation with new validation analysis

NASA Astrophysics Data System (ADS)

Hardie, Russell C.; Power, Jonathan D.; LeMaster, Daniel A.; Droege, Douglas R.; Gladysz, Szymon; Bose-Pillai, Santasri

2017-07-01

We present a numerical wave propagation method for simulating imaging of an extended scene under anisoplanatic conditions. While isoplanatic simulation is relatively common, few tools are specifically designed for simulating the imaging of extended scenes under anisoplanatic conditions. We provide a complete description of the proposed simulation tool, including the wave propagation method used. Our approach computes an array of point spread functions (PSFs) for a two-dimensional grid on the object plane. The PSFs are then used in a spatially varying weighted sum operation, with an ideal image, to produce a simulated image with realistic optical turbulence degradation. The degradation includes spatially varying warping and blurring. To produce the PSF array, we generate a series of extended phase screens. Simulated point sources are numerically propagated from an array of positions on the object plane, through the phase screens, and ultimately to the focal plane of the simulated camera. Note that the optical path for each PSF will be different, and thus, pass through a different portion of the extended phase screens. These different paths give rise to a spatially varying PSF to produce anisoplanatic effects. We use a method for defining the individual phase screen statistics that we have not seen used in previous anisoplanatic simulations. We also present a validation analysis. In particular, we compare simulated outputs with the theoretical anisoplanatic tilt correlation and a derived differential tilt variance statistic. This is in addition to comparing the long- and short-exposure PSFs and isoplanatic angle. We believe this analysis represents the most thorough validation of an anisoplanatic simulation to date. The current work is also unique that we simulate and validate both constant and varying Cn2(z) profiles. Furthermore, we simulate sequences with both temporally independent and temporally correlated turbulence effects. Temporal correlation is introduced by generating even larger extended phase screens and translating this block of screens in front of the propagation area. Our validation analysis shows an excellent match between the simulation statistics and the theoretical predictions. Thus, we think this tool can be used effectively to study optical anisoplanatic turbulence and to aid in the development of image restoration methods.

Chandra Interactive Analysis of Observations (CIAO)

NASA Technical Reports Server (NTRS)

Dobrzycki, Adam

2000-01-01

The Chandra (formerly AXAF) telescope, launched on July 23, 1999, provides X-rays data with unprecedented spatial and spectral resolution. As part of the Chandra scientific support, the Chandra X-ray Observatory Center provides a new data analysis system, CIAO ("Chandra Interactive Analysis of Observations"). We will present the main components of the system: "First Look" analysis; SHERPA: a multi-dimensional, multi-mission modeling and fitting application; Chandra Imaging and Plotting System; Detect package-source detection algorithms; and DM package generic data manipulation tools, We will set up a demonstration of the portable version of the system and show examples of Chandra Data Analysis.

Your Personal Analysis Toolkit - An Open Source Solution

NASA Astrophysics Data System (ADS)

Mitchell, T.

2009-12-01

Open source software is commonly known for its web browsers, word processors and programming languages. However, there is a vast array of open source software focused on geographic information management and geospatial application building in general. As geo-professionals, having easy access to tools for our jobs is crucial. Open source software provides the opportunity to add a tool to your tool belt and carry it with you for your entire career - with no license fees, a supportive community and the opportunity to test, adopt and upgrade at your own pace. OSGeo is a US registered non-profit representing more than a dozen mature geospatial data management applications and programming resources. Tools cover areas such as desktop GIS, web-based mapping frameworks, metadata cataloging, spatial database analysis, image processing and more. Learn about some of these tools as they apply to AGU members, as well as how you can join OSGeo and its members in getting the job done with powerful open source tools. If you haven't heard of OSSIM, MapServer, OpenLayers, PostGIS, GRASS GIS or the many other projects under our umbrella - then you need to hear this talk. Invest in yourself - use open source!

The Role of Motor Learning in Spatial Adaptation near a Tool

PubMed Central

Brown, Liana E.; Doole, Robert; Malfait, Nicole

2011-01-01

Some visual-tactile (bimodal) cells have visual receptive fields (vRFs) that overlap and extend moderately beyond the skin of the hand. Neurophysiological evidence suggests, however, that a vRF will grow to encompass a hand-held tool following active tool use but not after passive holding. Why does active tool use, and not passive holding, lead to spatial adaptation near a tool? We asked whether spatial adaptation could be the result of motor or visual experience with the tool, and we distinguished between these alternatives by isolating motor from visual experience with the tool. Participants learned to use a novel, weighted tool. The active training group received both motor and visual experience with the tool, the passive training group received visual experience with the tool, but no motor experience, and finally, a no-training control group received neither visual nor motor experience using the tool. After training, we used a cueing paradigm to measure how quickly participants detected targets, varying whether the tool was placed near or far from the target display. Only the active training group detected targets more quickly when the tool was placed near, rather than far, from the target display. This effect of tool location was not present for either the passive-training or control groups. These results suggest that motor learning influences how visual space around the tool is represented. PMID:22174944

Theory and investigation of acoustic multiple-input multiple-output systems based on spherical arrays in a room.

PubMed

Morgenstern, Hai; Rafaely, Boaz; Zotter, Franz

2015-11-01

Spatial attributes of room acoustics have been widely studied using microphone and loudspeaker arrays. However, systems that combine both arrays, referred to as multiple-input multiple-output (MIMO) systems, have only been studied to a limited degree in this context. These systems can potentially provide a powerful tool for room acoustics analysis due to the ability to simultaneously control both arrays. This paper offers a theoretical framework for the spatial analysis of enclosed sound fields using a MIMO system comprising spherical loudspeaker and microphone arrays. A system transfer function is formulated in matrix form for free-field conditions, and its properties are studied using tools from linear algebra. The system is shown to have unit-rank, regardless of the array types, and its singular vectors are related to the directions of arrival and radiation at the microphone and loudspeaker arrays, respectively. The formulation is then generalized to apply to rooms, using an image source method. In this case, the rank of the system is related to the number of significant reflections. The paper ends with simulation studies, which support the developed theory, and with an extensive reflection analysis of a room impulse response, using the platform of a MIMO system.

Close-Packed Silicon Microelectrodes for Scalable Spatially Oversampled Neural Recording

PubMed Central

Scholvin, Jörg; Kinney, Justin P.; Bernstein, Jacob G.; Moore-Kochlacs, Caroline; Kopell, Nancy; Fonstad, Clifton G.; Boyden, Edward S.

2015-01-01

Objective Neural recording electrodes are important tools for understanding neural codes and brain dynamics. Neural electrodes that are close-packed, such as in tetrodes, enable spatial oversampling of neural activity, which facilitates data analysis. Here we present the design and implementation of close-packed silicon microelectrodes, to enable spatially oversampled recording of neural activity in a scalable fashion. Methods Our probes are fabricated in a hybrid lithography process, resulting in a dense array of recording sites connected to submicron dimension wiring. Results We demonstrate an implementation of a probe comprising 1000 electrode pads, each 9 × 9 μm, at a pitch of 11 μm. We introduce design automation and packaging methods that allow us to readily create a large variety of different designs. Significance Finally, we perform neural recordings with such probes in the live mammalian brain that illustrate the spatial oversampling potential of closely packed electrode sites. PMID:26699649

Videogame interventions and spatial ability interactions.

PubMed

Redick, Thomas S; Webster, Sean B

2014-01-01

Numerous research studies have been conducted on the use of videogames as tools to improve one's cognitive abilities. While meta-analyses and qualitative reviews have provided evidence that some aspects of cognition such as spatial imagery are modified after exposure to videogames, other evidence has shown that matrix reasoning measures of fluid intelligence do not show evidence of transfer from videogame training. In the current work, we investigate the available evidence for transfer specifically to nonverbal intelligence and spatial ability measures, given recent research that these abilities may be most sensitive to training on cognitive and working memory tasks. Accordingly, we highlight a few studies that on the surface provide evidence for transfer to spatial abilities, but a closer look at the pattern of data does not reveal a clean interpretation of the results. We discuss the implications of these results in relation to research design and statistical analysis practices.

Videogame interventions and spatial ability interactions

PubMed Central

Redick, Thomas S.; Webster, Sean B.

2014-01-01

Numerous research studies have been conducted on the use of videogames as tools to improve one’s cognitive abilities. While meta-analyses and qualitative reviews have provided evidence that some aspects of cognition such as spatial imagery are modified after exposure to videogames, other evidence has shown that matrix reasoning measures of fluid intelligence do not show evidence of transfer from videogame training. In the current work, we investigate the available evidence for transfer specifically to nonverbal intelligence and spatial ability measures, given recent research that these abilities may be most sensitive to training on cognitive and working memory tasks. Accordingly, we highlight a few studies that on the surface provide evidence for transfer to spatial abilities, but a closer look at the pattern of data does not reveal a clean interpretation of the results. We discuss the implications of these results in relation to research design and statistical analysis practices. PMID:24723880

Endogenous synchronous fluorescence spectroscopy (SFS) of basal cell carcinoma-initial study

NASA Astrophysics Data System (ADS)

Borisova, E.; Zhelyazkova, Al.; Keremedchiev, M.; Penkov, N.; Semyachkina-Glushkovskaya, O.; Avramov, L.

2016-01-01

The human skin is a complex, multilayered and inhomogeneous organ with spatially varying optical properties. Analysis of cutaneous fluorescence spectra could be a very complicated task; therefore researchers apply complex mathematical tools for data evaluation, or try to find some specific approaches, that would simplify the spectral analysis. Synchronous fluorescence spectroscopy (SFS) allows improving the spectral resolution, which could be useful for the biological tissue fluorescence characterization and could increase the tumour detection diagnostic accuracy.

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

PubMed

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

2017-12-11

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

Violence in public transportation: an approach based on spatial analysis

PubMed Central

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

2017-01-01

ABSTRACT OBJECTIVE To carry out a spatial analysis of the occurrence of acts of violence (specifically robberies) in public transportation, identifying the regions of greater incidence, using geostatistics, and possible causes with the aid of a multicriteria analysis in the Geographic Information System. METHODS The unit of analysis is the traffic analysis zone of the survey named Origem-Destino, carried out in Salvador, state of Bahia, in 2013. The robberies recorded by the Department of Public Security of Bahia in 2013 were located and made compatible with the limits of the traffic analysis zones and, later, associated with the respective centroids. After determining the regions with the highest probability of robbery, we carried out a geographic analysis of the possible causes in the region with the highest robbery potential, considering the factors analyzed using a multicriteria analysis in a Geographic Information System environment. RESULTS The execution of the two steps of this study allowed us to identify areas corresponding to the greater probability of occurrence of robberies in public transportation. In addition, the three most vulnerable road sections (Estrada da Liberdade, Rua Pero Vaz, and Avenida General San Martin) were identified in these areas. In these sections, the factors that most contribute with the potential for robbery in buses are: F1 - proximity to places that facilitate escape, F3 - great movement of persons, and F2 - absence of policing, respectively. CONCLUSIONS Indicator Kriging (geostatistical estimation) can be used to construct a spatial probability surface, which can be a useful tool for the implementation of public policies. The multicriteria analysis in the Geographic Information System environment allowed us to understand the spatial factors related to the phenomenon under analysis. PMID:29236883

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

PubMed

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

2001-05-01

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

Spatial-Temporal Dynamics of Urban Fire Incidents: a Case Study of Nanjing, China

NASA Astrophysics Data System (ADS)

Yao, J.; Zhang, X.

2016-06-01

Fire and rescue service is one of the fundamental public services provided by government in order to protect people, properties and environment from fires and other disasters, and thus promote a safer living environment. Well understanding spatial-temporal dynamics of fire incidents can offer insights for potential determinants of various fire events and enable better fire risk estimation, assisting future allocation of prevention resources and strategic planning of mitigation programs. Using a 12-year (2002-2013) dataset containing the urban fire events in Nanjing, China, this research explores the spatial-temporal dynamics of urban fire incidents. A range of exploratory spatial data analysis (ESDA) approaches and tools, such as spatial kernel density and co-maps, are employed to examine the spatial, temporal and spatial-temporal variations of the fire events. Particular attention has been paid to two types of fire incidents: residential properties and local facilities, due to their relatively higher occurrence frequencies. The results demonstrated that the amount of urban fire has greatly increased in the last decade and spatial-temporal distribution of fire events vary among different incident types, which implies varying impact of potential influencing factors for further investigation.

Computational models of spatial updating in peri-saccadic perception

PubMed Central

Hamker, Fred H.; Zirnsak, Marc; Ziesche, Arnold; Lappe, Markus

2011-01-01

Perceptual phenomena that occur around the time of a saccade, such as peri-saccadic mislocalization or saccadic suppression of displacement, have often been linked to mechanisms of spatial stability. These phenomena are usually regarded as errors in processes of trans-saccadic spatial transformations and they provide important tools to study these processes. However, a true understanding of the underlying brain processes that participate in the preparation for a saccade and in the transfer of information across it requires a closer, more quantitative approach that links different perceptual phenomena with each other and with the functional requirements of ensuring spatial stability. We review a number of computational models of peri-saccadic spatial perception that provide steps in that direction. Although most models are concerned with only specific phenomena, some generalization and interconnection between them can be obtained from a comparison. Our analysis shows how different perceptual effects can coherently be brought together and linked back to neuronal mechanisms on the way to explaining vision across saccades. PMID:21242143

Improved application of independent component analysis to functional magnetic resonance imaging study via linear projection techniques.

PubMed

Long, Zhiying; Chen, Kewei; Wu, Xia; Reiman, Eric; Peng, Danling; Yao, Li

2009-02-01

Spatial Independent component analysis (sICA) has been widely used to analyze functional magnetic resonance imaging (fMRI) data. The well accepted implicit assumption is the spatially statistical independency of intrinsic sources identified by sICA, making the sICA applications difficult for data in which there exist interdependent sources and confounding factors. This interdependency can arise, for instance, from fMRI studies investigating two tasks in a single session. In this study, we introduced a linear projection approach and considered its utilization as a tool to separate task-related components from two-task fMRI data. The robustness and feasibility of the method are substantiated through simulation on computer data and fMRI real rest data. Both simulated and real two-task fMRI experiments demonstrated that sICA in combination with the projection method succeeded in separating spatially dependent components and had better detection power than pure model-based method when estimating activation induced by each task as well as both tasks.

An inverse method for determining the spatially resolved properties of viscoelastic–viscoplastic three-dimensional printed materials

PubMed Central

Chen, X.; Ashcroft, I. A.; Wildman, R. D.; Tuck, C. J.

2015-01-01

A method using experimental nanoindentation and inverse finite-element analysis (FEA) has been developed that enables the spatial variation of material constitutive properties to be accurately determined. The method was used to measure property variation in a three-dimensional printed (3DP) polymeric material. The accuracy of the method is dependent on the applicability of the constitutive model used in the inverse FEA, hence four potential material models: viscoelastic, viscoelastic–viscoplastic, nonlinear viscoelastic and nonlinear viscoelastic–viscoplastic were evaluated, with the latter enabling the best fit to experimental data. Significant changes in material properties were seen in the depth direction of the 3DP sample, which could be linked to the degree of cross-linking within the material, a feature inherent in a UV-cured layer-by-layer construction method. It is proposed that the method is a powerful tool in the analysis of manufacturing processes with potential spatial property variation that will also enable the accurate prediction of final manufactured part performance. PMID:26730216

An inverse method for determining the spatially resolved properties of viscoelastic-viscoplastic three-dimensional printed materials.

PubMed

Chen, X; Ashcroft, I A; Wildman, R D; Tuck, C J

2015-11-08

A method using experimental nanoindentation and inverse finite-element analysis (FEA) has been developed that enables the spatial variation of material constitutive properties to be accurately determined. The method was used to measure property variation in a three-dimensional printed (3DP) polymeric material. The accuracy of the method is dependent on the applicability of the constitutive model used in the inverse FEA, hence four potential material models: viscoelastic, viscoelastic-viscoplastic, nonlinear viscoelastic and nonlinear viscoelastic-viscoplastic were evaluated, with the latter enabling the best fit to experimental data. Significant changes in material properties were seen in the depth direction of the 3DP sample, which could be linked to the degree of cross-linking within the material, a feature inherent in a UV-cured layer-by-layer construction method. It is proposed that the method is a powerful tool in the analysis of manufacturing processes with potential spatial property variation that will also enable the accurate prediction of final manufactured part performance.

Transcriptome In Vivo Analysis (TIVA) of spatially defined single cells in intact live mouse and human brain tissue

PubMed Central

Lovatt, Ditte; Ruble, Brittani K.; Lee, Jaehee; Dueck, Hannah; Kim, Tae Kyung; Fisher, Stephen; Francis, Chantal; Spaethling, Jennifer M.; Wolf, John A.; Grady, M. Sean; Ulyanova, Alexandra V.; Yeldell, Sean B.; Griepenburg, Julianne C.; Buckley, Peter T.; Kim, Junhyong; Sul, Jai-Yoon; Dmochowski, Ivan J.; Eberwine, James

2014-01-01

Transcriptome profiling is an indispensable tool in advancing the understanding of single cell biology, but depends upon methods capable of isolating mRNA at the spatial resolution of a single cell. Current capture methods lack sufficient spatial resolution to isolate mRNA from individual in vivo resident cells without damaging adjacent tissue. Because of this limitation, it has been difficult to assess the influence of the microenvironment on the transcriptome of individual neurons. Here, we engineered a Transcriptome In Vivo Analysis (TIVA)-tag, which upon photoactivation enables mRNA capture from single cells in live tissue. Using the TIVA-tag in combination with RNA-seq to analyze transcriptome variance among single dispersed cells and in vivo resident mouse and human neurons, we show that the tissue microenvironment shapes the transcriptomic landscape of individual cells. The TIVA methodology provides the first noninvasive approach for capturing mRNA from single cells in their natural microenvironment. PMID:24412976

Development and Evaluation of a Web Map Mind Tool Environment with the Theory of Spatial Thinking and Project-Based Learning Strategy

ERIC Educational Resources Information Center

Hou, Huei-Tse; Yu, Tsai-Fang; Wu, Yi-Xuan; Sung, Yao-Ting; Chang, Kuo-En

2016-01-01

The theory of spatial thinking is relevant to the learning and teaching of many academic domains. One promising method to facilitate learners' higher-order thinking is to utilize a web map mind tool to assist learners in applying spatial thinking to cooperative problem solving. In this study, an environment is designed based on the theory of…

Eulerian frequency analysis of structural vibrations from high-speed video

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

Venanzoni, Andrea; Siemens Industry Software NV, Interleuvenlaan 68, B-3001 Leuven; De Ryck, Laurent

An approach for the analysis of the frequency content of structural vibrations from high-speed video recordings is proposed. The techniques and tools proposed rely on an Eulerian approach, that is, using the time history of pixels independently to analyse structural motion, as opposed to Lagrangian approaches, where the motion of the structure is tracked in time. The starting point is an existing Eulerian motion magnification method, which consists in decomposing the video frames into a set of spatial scales through a so-called Laplacian pyramid [1]. Each scale — or level — can be amplified independently to reconstruct a magnified motionmore » of the observed structure. The approach proposed here provides two analysis tools or pre-amplification steps. The first tool provides a representation of the global frequency content of a video per pyramid level. This may be further enhanced by applying an angular filter in the spatial frequency domain to each frame of the video before the Laplacian pyramid decomposition, which allows for the identification of the frequency content of the structural vibrations in a particular direction of space. This proposed tool complements the existing Eulerian magnification method by amplifying selectively the levels containing relevant motion information with respect to their frequency content. This magnifies the displacement while limiting the noise contribution. The second tool is a holographic representation of the frequency content of a vibrating structure, yielding a map of the predominant frequency components across the structure. In contrast to the global frequency content representation of the video, this tool provides a local analysis of the periodic gray scale intensity changes of the frame in order to identify the vibrating parts of the structure and their main frequencies. Validation cases are provided and the advantages and limits of the approaches are discussed. The first validation case consists of the frequency content retrieval of the tip of a shaker, excited at selected fixed frequencies. The goal of this setup is to retrieve the frequencies at which the tip is excited. The second validation case consists of two thin metal beams connected to a randomly excited bar. It is shown that the holographic representation visually highlights the predominant frequency content of each pixel and locates the global frequencies of the motion, thus retrieving the natural frequencies for each beam.« less

Computational tool for the early screening of monoclonal antibodies for their viscosities

PubMed Central

Agrawal, Neeraj J; Helk, Bernhard; Kumar, Sandeep; Mody, Neil; Sathish, Hasige A.; Samra, Hardeep S.; Buck, Patrick M; Li, Li; Trout, Bernhardt L

2016-01-01

Highly concentrated antibody solutions often exhibit high viscosities, which present a number of challenges for antibody-drug development, manufacturing and administration. The antibody sequence is a key determinant for high viscosity of highly concentrated solutions; therefore, a sequence- or structure-based tool that can identify highly viscous antibodies from their sequence would be effective in ensuring that only antibodies with low viscosity progress to the development phase. Here, we present a spatial charge map (SCM) tool that can accurately identify highly viscous antibodies from their sequence alone (using homology modeling to determine the 3-dimensional structures). The SCM tool has been extensively validated at 3 different organizations, and has proved successful in correctly identifying highly viscous antibodies. As a quantitative tool, SCM is amenable to high-throughput automated analysis, and can be effectively implemented during the antibody screening or engineering phase for the selection of low-viscosity antibodies. PMID:26399600

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

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

Hu, Rui

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for amore » wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.« less

A fully-implicit high-order system thermal-hydraulics model for advanced non-LWR safety analyses

DOE PAGES

Hu, Rui

2016-11-19

An advanced system analysis tool is being developed for advanced reactor safety analysis. This paper describes the underlying physics and numerical models used in the code, including the governing equations, the stabilization schemes, the high-order spatial and temporal discretization schemes, and the Jacobian Free Newton Krylov solution method. The effects of the spatial and temporal discretization schemes are investigated. Additionally, a series of verification test problems are presented to confirm the high-order schemes. Furthermore, it is demonstrated that the developed system thermal-hydraulics model can be strictly verified with the theoretical convergence rates, and that it performs very well for amore » wide range of flow problems with high accuracy, efficiency, and minimal numerical diffusions.« less

Open source GIS based tools to improve hydrochemical water resources management in EU H2020 FREEWAT platform

NASA Astrophysics Data System (ADS)

Criollo, Rotman; Velasco, Violeta; Vázquez-Suñé, Enric; Nardi, Albert; Marazuela, Miguel A.; Rossetto, Rudy; Borsi, Iacopo; Foglia, Laura; Cannata, Massimiliano; De Filippis, Giovanna

2017-04-01

Due to the general increase of water scarcity (Steduto et al., 2012), water quantity and quality must be well known to ensure a proper access to water resources in compliance with local and regional directives. This circumstance can be supported by tools which facilitate process of data management and its analysis. Such analyses have to provide research/professionals, policy makers and users with the ability to improve the management of the water resources with standard regulatory guidelines. Compliance with the established standard regulatory guidelines (with a special focus on requirement deriving from the GWD) should have an effective monitoring, evaluation, and interpretation of a large number of physical and chemical parameters. These amounts of datasets have to be assessed and interpreted: (i) integrating data from different sources and gathered with different data access techniques and formats; (ii) managing data with varying temporal and spatial extent; (iii) integrating groundwater quality information with other relevant information such as further hydrogeological data (Velasco et al., 2014) and pre-processing these data generally for the realization of groundwater models. In this context, the Hydrochemical Analysis Tools, akvaGIS Tools, has been implemented within the H2020 FREEWAT project; which aims to manage water resources by modelling water resource management in an open source GIS platform (QGIS desktop). The main goal of AkvaGIS Tools is to improve water quality analysis through different capabilities to improve the case study conceptual model managing all data related into its geospatial database (implemented in Spatialite) and a set of tools for improving the harmonization, integration, standardization, visualization and interpretation of the hydrochemical data. To achieve that, different commands cover a wide range of methodologies for querying, interpreting, and comparing groundwater quality data and facilitate the pre-processing analysis for being used in the realization of groundwater modelling. They include, ionic balance calculations, chemical time-series analysis, correlation of chemical parameters, and calculation of various common hydrochemical diagrams (Salinity, Schöeller-Berkaloff, Piper, and Stiff), among others. Furthermore, it allows the generation of maps of the spatial distributions of parameters and diagrams and thematic maps for the parameters measured and classified in the queried area. References: Rossetto R., Borsi I., Schifani C., Bonari E., Mogorovich P., Primicerio M. (2013). SID&GRID: Integrating hydrological modeling in GIS environment. Rendiconti Online Societa Geologica Italiana, Vol. 24, 282-283 Steduto, P., Faurès, J.M., Hoogeveen, J., Winpenny, J.T., Burke, J.J. (2012). Coping with water scarcity: an action framework for agriculture and food security. ISSN 1020-1203 ; 38 Velasco, V., Tubau, I., Vázquez-Suñé, E., Gogu, R., Gaitanaru, D., Alcaraz, M., Sanchez-Vila, X. (2014). GIS-based hydrogeochemical analysis tools (QUIMET). Computers & Geosciences, 70, 164-180.

Spatial and thematic assessment of object-based forest stand delineation using an OFA-matrix

NASA Astrophysics Data System (ADS)

Hernando, A.; Tiede, D.; Albrecht, F.; Lang, S.

2012-10-01

The delineation and classification of forest stands is a crucial aspect of forest management. Object-based image analysis (OBIA) can be used to produce detailed maps of forest stands from either orthophotos or very high resolution satellite imagery. However, measures are then required for evaluating and quantifying both the spatial and thematic accuracy of the OBIA output. In this paper we present an approach for delineating forest stands and a new Object Fate Analysis (OFA) matrix for accuracy assessment. A two-level object-based orthophoto analysis was first carried out to delineate stands on the Dehesa Boyal public land in central Spain (Avila Province). Two structural features were first created for use in class modelling, enabling good differentiation between stands: a relational tree cover cluster feature, and an arithmetic ratio shadow/tree feature. We then extended the OFA comparison approach with an OFA-matrix to enable concurrent validation of thematic and spatial accuracies. Its diagonal shows the proportion of spatial and thematic coincidence between a reference data and the corresponding classification. New parameters for Spatial Thematic Loyalty (STL), Spatial Thematic Loyalty Overall (STLOVERALL) and Maximal Interfering Object (MIO) are introduced to summarise the OFA-matrix accuracy assessment. A stands map generated by OBIA (classification data) was compared with a map of the same area produced from photo interpretation and field data (reference data). In our example the OFA-matrix results indicate good spatial and thematic accuracies (>65%) for all stand classes except for the shrub stands (31.8%), and a good STLOVERALL (69.8%). The OFA-matrix has therefore been shown to be a valid tool for OBIA accuracy assessment.

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

PubMed

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

2018-03-13

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

Weathering the Storm: Developing a Spatial Data Infrastructure and Online Research Platform for Oil Spill Preparedness

NASA Astrophysics Data System (ADS)

Bauer, J. R.; Rose, K.; Romeo, L.; Barkhurst, A.; Nelson, J.; Duran-Sesin, R.; Vielma, J.

2016-12-01

Efforts to prepare for and reduce the risk of hazards, from both natural and anthropogenic sources, which threaten our oceans and coasts requires an understanding of the dynamics and interactions between the physical, ecological, and socio-economic systems. Understanding these coupled dynamics are essential as offshore oil & gas exploration and production continues to push into harsher, more extreme environments where risks and uncertainty increase. However, working with these large, complex data from various sources and scales to assess risks and potential impacts associated with offshore energy exploration and production poses several challenges to research. In order to address these challenges, an integrated assessment model (IAM) was developed at the Department of Energy's (DOE) National Energy Technology Laboratory (NETL) that combines spatial data infrastructure and an online research platform to manage, process, analyze, and share these large, multidimensional datasets, research products, and the tools and models used to evaluate risk and reduce uncertainty for the entire offshore system, from the subsurface, through the water column, to coastal ecosystems and communities. Here, we will discuss the spatial data infrastructure and online research platform, NETL's Energy Data eXchange (EDX), that underpin the offshore IAM, providing information on how the framework combines multidimensional spatial data and spatio-temporal tools to evaluate risks to the complex matrix of potential environmental, social, and economic impacts stemming from modeled offshore hazard scenarios, such as oil spills or hurricanes. In addition, we will discuss the online analytics, tools, and visualization methods integrated into this framework that support availability and access to data, as well as allow for the rapid analysis and effective communication of analytical results to aid a range of decision-making needs.

Analysis of cardiac signals using spatial filling index and time-frequency domain

PubMed Central

Faust, Oliver; Acharya U, Rajendra; Krishnan, SM; Min, Lim Choo

2004-01-01

Background Analysis of heart rate variation (HRV) has become a popular noninvasive tool for assessing the activities of the autonomic nervous system (ANS). HRV analysis is based on the concept that fast fluctuations may specifically reflect changes of sympathetic and vagal activity. It shows that the structure generating the signal is not simply linear, but also involves nonlinear contributions. These signals are essentially non-stationary; may contain indicators of current disease, or even warnings about impending diseases. The indicators may be present at all times or may occur at random in the time scale. However, to study and pinpoint abnormalities in voluminous data collected over several hours is strenuous and time consuming. Methods This paper presents the spatial filling index and time-frequency analysis of heart rate variability signal for disease identification. Renyi's entropy is evaluated for the signal in the Wigner-Ville and Continuous Wavelet Transformation (CWT) domain. Results This Renyi's entropy gives lower 'p' value for scalogram than Wigner-Ville distribution and also, the contours of scalogram visually show the features of the diseases. And in the time-frequency analysis, the Renyi's entropy gives better result for scalogram than the Wigner-Ville distribution. Conclusion Spatial filling index and Renyi's entropy has distinct regions for various diseases with an accuracy of more than 95%. PMID:15361254

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

PubMed

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

2011-01-01

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

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

PubMed

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

2009-04-22

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

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

PubMed Central

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

2009-01-01

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

Multiplexing 200 spatial modes with a single hologram

NASA Astrophysics Data System (ADS)

Rosales-Guzmán, Carmelo; Bhebhe, Nkosiphile; Mahonisi, Nyiku; Forbes, Andrew

2017-11-01

The on-demand tailoring of light's spatial shape is of great relevance in a wide variety of research areas. Computer-controlled devices, such as spatial light modulators (SLMs) or digital micromirror devices, offer a very accurate, flexible and fast holographic means to this end. Remarkably, digital holography affords the simultaneous generation of multiple beams (multiplexing), a tool with numerous applications in many fields. Here, we provide a self-contained tutorial on light beam multiplexing. Through the use of several examples, the readers will be guided step by step in the process of light beam shaping and multiplexing. Additionally, we provide a quantitative analysis on the multiplexing capabilities of SLMs to assess the maximum number of beams that can be multiplexed on a single SLM, showing approximately 200 modes on a single hologram.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2017-12-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Quantitative evaluation of the risk induced by dominant geomorphological processes on different land uses, based on GIS spatial analysis models

NASA Astrophysics Data System (ADS)

Ştefan, Bilaşco; Sanda, Roşca; Ioan, Fodorean; Iuliu, Vescan; Sorin, Filip; Dănuţ, Petrea

2018-06-01

Maramureş Land is mostly characterized by agricultural and forestry land use due to its specific configuration of topography and its specific pedoclimatic conditions. Taking into consideration the trend of the last century from the perspective of land management, a decrease in the surface of agricultural lands to the advantage of built-up and grass lands, as well as an accelerated decrease in the forest cover due to uncontrolled and irrational forest exploitation, has become obvious. The field analysis performed on the territory of Maramureş Land has highlighted a high frequency of two geomorphologic processes — landslides and soil erosion — which have a major negative impact on land use due to their rate of occurrence. The main aim of the present study is the GIS modeling of the two geomorphologic processes, determining a state of vulnerability (the USLE model for soil erosion and a quantitative model based on the morphometric characteristics of the territory, derived from the HG. 447/2003) and their integration in a complex model of cumulated vulnerability identification. The modeling of the risk exposure was performed using a quantitative approach based on models and equations of spatial analysis, which were developed with modeled raster data structures and primary vector data, through a matrix highlighting the correspondence between vulnerability and land use classes. The quantitative analysis of the risk was performed by taking into consideration the exposure classes as modeled databases and the land price as a primary alphanumeric database using spatial analysis techniques for each class by means of the attribute table. The spatial results highlight the territories with a high risk to present geomorphologic processes that have a high degree of occurrence and represent a useful tool in the process of spatial planning.

Mapping of species richness for conservation of biological diversity: conceptual and methodological issues

Treesearch

M.J. Conroy; B.R. Noon

1996-01-01

Biodiversity mapping (e.g., the Gap Analysis Program [GAP]), in which vegetative features and categories of land use are mapped at coarse spatial scales, has been proposed as a reliable tool for land use decisions (e.g., reserve identification, selection, and design). This implicitly assumes that species richness data collected at coarse spatiotemporal scales provide a...

Analyzing long-term changes in vegetation with geographic information system and remotely sensed data

Treesearch

Louis. R. Iverson; Paul. G. Risser; Paul. G. Risser

1987-01-01

Geographic information systems and remote sensing techniques are powerful tools in the analysis of long-term changes in vegetation and land use, especially because spatial information from two or more time intervals can be compared more readily than by manual methods. A primary restriction is the paucity of data that has been digitized from earlier periods. The...

Teleworking and Globalisation. Towards a Methodology for Mapping and Measuring the Emerging Global Division of Labour in the Information Economy.

ERIC Educational Resources Information Center

Huws, Ursula; Jagger, Nick; O'Regan, Siobhan

Inexpensive telecommunications, the spread of computing, and globalization are creating major change in the location of work within and between countries. Because no tools have yet been developed to investigate the new spatial employment patterns, a cluster analysis involving more than 50 variables and 206 countries was performed to group…

The Spectral Image Processing System (SIPS): Software for integrated analysis of AVIRIS data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1992-01-01

The Spectral Image Processing System (SIPS) is a software package developed by the Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, in response to a perceived need to provide integrated tools for analysis of imaging spectrometer data both spectrally and spatially. SIPS was specifically designed to deal with data from the Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) and the High Resolution Imaging Spectrometer (HIRIS), but was tested with other datasets including the Geophysical and Environmental Research Imaging Spectrometer (GERIS), GEOSCAN images, and Landsat TM. SIPS was developed using the 'Interactive Data Language' (IDL). It takes advantage of high speed disk access and fast processors running under the UNIX operating system to provide rapid analysis of entire imaging spectrometer datasets. SIPS allows analysis of single or multiple imaging spectrometer data segments at full spatial and spectral resolution. It also allows visualization and interactive analysis of image cubes derived from quantitative analysis procedures such as absorption band characterization and spectral unmixing. SIPS consists of three modules: SIPS Utilities, SIPS_View, and SIPS Analysis. SIPS version 1.1 is described below.

An Object-Based Approach to Evaluation of Climate Variability Projections and Predictions

NASA Astrophysics Data System (ADS)

Ammann, C. M.; Brown, B.; Kalb, C. P.; Bullock, R.

2017-12-01

Evaluations of the performance of earth system model predictions and projections are of critical importance to enhance usefulness of these products. Such evaluations need to address specific concerns depending on the system and decisions of interest; hence, evaluation tools must be tailored to inform about specific issues. Traditional approaches that summarize grid-based comparisons of analyses and models, or between current and future climate, often do not reveal important information about the models' performance (e.g., spatial or temporal displacements; the reason behind a poor score) and are unable to accommodate these specific information needs. For example, summary statistics such as the correlation coefficient or the mean-squared error provide minimal information to developers, users, and decision makers regarding what is "right" and "wrong" with a model. New spatial and temporal-spatial object-based tools from the field of weather forecast verification (where comparisons typically focus on much finer temporal and spatial scales) have been adapted to more completely answer some of the important earth system model evaluation questions. In particular, the Method for Object-based Diagnostic Evaluation (MODE) tool and its temporal (three-dimensional) extension (MODE-TD) have been adapted for these evaluations. More specifically, these tools can be used to address spatial and temporal displacements in projections of El Nino-related precipitation and/or temperature anomalies, ITCZ-associated precipitation areas, atmospheric rivers, seasonal sea-ice extent, and other features of interest. Examples of several applications of these tools in a climate context will be presented, using output of the CESM large ensemble. In general, these tools provide diagnostic information about model performance - accounting for spatial, temporal, and intensity differences - that cannot be achieved using traditional (scalar) model comparison approaches. Thus, they can provide more meaningful information that can be used in decision-making and planning. Future extensions and applications of these tools in a climate context will be considered.

A Review and Framework for Categorizing Current Research and Development in Health Related Geographical Information Systems (GIS) Studies.

PubMed

Lyseen, A K; Nøhr, C; Sørensen, E M; Gudes, O; Geraghty, E M; Shaw, N T; Bivona-Tellez, C

2014-08-15

The application of GIS in health science has increased over the last decade and new innovative application areas have emerged. This study reviews the literature and builds a framework to provide a conceptual overview of the domain, and to promote strategic planning for further research of GIS in health. The framework is based on literature from the library databases Scopus and Web of Science. The articles were identified based on keywords and initially selected for further study based on titles and abstracts. A grounded theory-inspired method was applied to categorize the selected articles in main focus areas. Subsequent frequency analysis was performed on the identified articles in areas of infectious and non-infectious diseases and continent of origin. A total of 865 articles were included. Four conceptual domains within GIS in health sciences comprise the framework: spatial analysis of disease, spatial analysis of health service planning, public health, health technologies and tools. Frequency analysis by disease status and location show that malaria and schistosomiasis are the most commonly analyzed infectious diseases where cancer and asthma are the most frequently analyzed non-infectious diseases. Across categories, articles from North America predominate, and in the category of spatial analysis of diseases an equal number of studies concern Asia. Spatial analysis of diseases and health service planning are well-established research areas. The development of future technologies and new application areas for GIS and data-gathering technologies such as GPS, smartphones, remote sensing etc. will be nudging the research in GIS and health.

A Review and Framework for Categorizing Current Research and Development in Health Related Geographical Information Systems (GIS) Studies

PubMed Central

Nøhr, C.; Sørensen, E. M.; Gudes, O.; Geraghty, E. M.; Shaw, N. T.; Bivona-Tellez, C.

2014-01-01

Summary Objectives The application of GIS in health science has increased over the last decade and new innovative application areas have emerged. This study reviews the literature and builds a framework to provide a conceptual overview of the domain, and to promote strategic planning for further research of GIS in health. Method The framework is based on literature from the library databases Scopus and Web of Science. The articles were identified based on keywords and initially selected for further study based on titles and abstracts. A grounded theory-inspired method was applied to categorize the selected articles in main focus areas. Subsequent frequency analysis was performed on the identified articles in areas of infectious and non-infectious diseases and continent of origin. Results A total of 865 articles were included. Four conceptual domains within GIS in health sciences comprise the framework: spatial analysis of disease, spatial analysis of health service planning, public health, health technologies and tools. Frequency analysis by disease status and location show that malaria and schistosomiasis are the most commonly analyzed infectious diseases where cancer and asthma are the most frequently analyzed non-infectious diseases. Across categories, articles from North America predominate, and in the category of spatial analysis of diseases an equal number of studies concern Asia. Conclusion Spatial analysis of diseases and health service planning are well-established research areas. The development of future technologies and new application areas for GIS and data-gathering technologies such as GPS, smartphones, remote sensing etc. will be nudging the research in GIS and health. PMID:25123730

Spatial Systems Lipidomics Reveals Nonalcoholic Fatty Liver Disease Heterogeneity

PubMed Central

2018-01-01

Hepatocellular lipid accumulation characterizes nonalcoholic fatty liver disease (NAFLD). However, the types of lipids associated with disease progression are debated, as is the impact of their localization. Traditional lipidomics analysis using liver homogenates or plasma dilutes and averages lipid concentrations, and does not provide spatial information about lipid distribution. We aimed to characterize the distribution of specific lipid species related to NAFLD severity by performing label-free molecular analysis by mass spectrometry imaging (MSI). Fresh frozen liver biopsies from obese subjects undergoing bariatric surgery (n = 23) with various degrees of NAFLD were cryosectioned and analyzed by matrix-assisted laser desorption/ionization (MALDI)-MSI. Molecular identification was verified by tandem MS. Tissue sections were histopathologically stained, annotated according to the Kleiner classification, and coregistered with the MSI data set. Lipid pathway analysis was performed and linked to local proteome networks. Spatially resolved lipid profiles showed pronounced differences between nonsteatotic and steatotic tissues. Lipid identification and network analyses revealed phosphatidylinositols and arachidonic acid metabolism in nonsteatotic regions, whereas low–density lipoprotein (LDL) and very low–density lipoprotein (VLDL) metabolism was associated with steatotic tissue. Supervised and unsupervised discriminant analysis using lipid based classifiers outperformed simulated analysis of liver tissue homogenates in predicting steatosis severity. We conclude that lipid composition of steatotic and nonsteatotic tissue is highly distinct, implying that spatial context is important for understanding the mechanisms of lipid accumulation in NAFLD. MSI combined with principal component–linear discriminant analysis linking lipid and protein pathways represents a novel tool enabling detailed, comprehensive studies of the heterogeneity of NAFLD. PMID:29570976

TOOLS FOR PRESENTING SPATIAL AND TEMPORAL PATTERNS OF ENVIRONMENTAL MONITORING DATA

EPA Science Inventory

The EPA Health Effects Research Laboratory has developed this data presentation tool for use with a variety of types of data which may contain spatial and temporal patterns of interest. he technology links mainframe computing power to the new generation of "desktop publishing" ha...

Interactive 3D Models and Simulations for Nuclear Security Education, Training, and Analysis.

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

Warner, David K.; Dickens, Brian Scott; Heimer, Donovan J.

By providing examples of products that have been produced in the past, it is the hopes of the authors that the audience will have a more thorough understanding of 3D modeling tools, potential applications, and capabilities that they can provide. Truly the applications and capabilities of these types of tools are only limited by one’s imagination. The future of three-dimensional models lies in the expansion into the world of virtual reality where one will experience a fully immersive first-person environment. The use of headsets and hand tools will allow students and instructors to have a more thorough spatial understanding ofmore » facilities and scenarios that they will encounter in the real world.« less

Geospatial Characterization of Fluvial Wood Arrangement in a Semi-confined Alluvial River

NASA Astrophysics Data System (ADS)

Martin, D. J.; Harden, C. P.; Pavlowsky, R. T.

2014-12-01

Large woody debris (LWD) has become universally recognized as an integral component of fluvial systems, and as a result, has become increasingly common as a river restoration tool. However, "natural" processes of wood recruitment and the subsequent arrangement of LWD within the river network are poorly understood. This research used a suite of spatial statistics to investigate longitudinal arrangement patterns of LWD in a low-gradient, Midwestern river. First, a large-scale GPS inventory of LWD, performed on the Big River in the eastern Missouri Ozarks, resulted in over 4,000 logged positions of LWD along seven river segments that covered nearly 100 km of the 237 km river system. A global Moran's I analysis indicates that LWD density is spatially autocorrelated and displays a clustering tendency within all seven river segments (P-value range = 0.000 to 0.054). A local Moran's I analysis identified specific locations along the segments where clustering occurs and revealed that, on average, clusters of LWD density (high or low) spanned 400 m. Spectral analyses revealed that, in some segments, LWD density is spatially periodic. Two segments displayed strong periodicity, while the remaining segments displayed varying degrees of noisiness. Periodicity showed a positive association with gravel bar spacing and meander wavelength, although there were insufficient data to statistically confirm the relationship. A wavelet analysis was then performed to investigate periodicity relative to location along the segment. The wavelet analysis identified significant (α = 0.05) periodicity at discrete locations along each of the segments. Those reaches yielding strong periodicity showed stronger relationships between LWD density and the geomorphic/riparian independent variables tested. Analyses consistently identified valley width and sinuosity as being associated with LWD density. The results of these analyses contribute a new perspective on the longitudinal distribution of LWD in a river system, which should help identify physical and/or riparian control mechanisms of LWD arrangement and support the development of models of LWD arrangement. Additionally, the spatial statistical tools presented here have shown to be valuable for identifying longitudinal patterns in river system components.

Reliable identification of deep sulcal pits: the effects of scan session, scanner, and surface extraction tool.

PubMed

Im, Kiho; Lee, Jong-Min; Jeon, Seun; Kim, Jong-Heon; Seo, Sang Won; Na, Duk L; Grant, P Ellen

2013-01-01

Sulcal pit analysis has been providing novel insights into brain function and development. The purpose of this study was to evaluate the reliability of sulcal pit extraction with respect to the effects of scan session, scanner, and surface extraction tool. Five subjects were scanned 4 times at 3 MRI centers and other 5 subjects were scanned 3 times at 2 MRI centers, including 1 test-retest session. Sulcal pits were extracted on the white matter surfaces reconstructed with both Montreal Neurological Institute and Freesurfer pipelines. We estimated similarity of the presence of sulcal pits having a maximum value of 1 and their spatial difference within the same subject. The tests showed high similarity of the sulcal pit presence and low spatial difference. The similarity was more than 0.90 and the spatial difference was less than 1.7 mm in most cases according to different scan sessions or scanners, and more than 0.85 and about 2.0 mm across surface extraction tools. The reliability of sulcal pit extraction was more affected by the image processing-related factors than the scan session or scanner factors. Moreover, the similarity of sulcal pit distribution appeared to be largely influenced by the presence or absence of the sulcal pits on the shallow and small folds. We suggest that our sulcal pit extraction from MRI is highly reliable and could be useful for clinical applications as an imaging biomarker.

Integration of remote sensing and GIS: Data and data access

USGS Publications Warehouse

Ehlers, M.; Greenlee, D.D.; Smith, T.; Star, J.

1991-01-01

CT: Theintegration of remote sensing tools and technology with the spatial analysis orientation of geographic information systems is a complex task. In this paper, we focus on the issues of making data available and useful to the user. In part, this involves a set of problems which reflect on the physical and logical structures used to encode the data. At the same time, however, the mechanisms and protocols which provide information about the data, and which maintain the data through time, have become increasingly important. We discuss these latter issues from the viewpoint of the functions which must be provided by archives of spatial data.

Spotting effect in microarray experiments

PubMed Central

Mary-Huard, Tristan; Daudin, Jean-Jacques; Robin, Stéphane; Bitton, Frédérique; Cabannes, Eric; Hilson, Pierre

2004-01-01

Background Microarray data must be normalized because they suffer from multiple biases. We have identified a source of spatial experimental variability that significantly affects data obtained with Cy3/Cy5 spotted glass arrays. It yields a periodic pattern altering both signal (Cy3/Cy5 ratio) and intensity across the array. Results Using the variogram, a geostatistical tool, we characterized the observed variability, called here the spotting effect because it most probably arises during steps in the array printing procedure. Conclusions The spotting effect is not appropriately corrected by current normalization methods, even by those addressing spatial variability. Importantly, the spotting effect may alter differential and clustering analysis. PMID:15151695

Spectro-microscopy of living plant cells.

PubMed

Harter, Klaus; Meixner, Alfred J; Schleifenbaum, Frank

2012-01-01

Spectro-microscopy, a combination of fluorescence microscopy with spatially resolved spectroscopic techniques, provides new and exciting tools for functional cell biology in living organisms. This review focuses on recent developments in spectro-microscopic applications for the investigation of living plant cells in their native tissue context. The application of spectro-microscopic methods led to the recent discovery of a fast signal response pathway for the brassinosteroide receptor BRI1 in the plasma membrane of living plant cells. Moreover, the competence of different plant cell types to respond to environmental or endogenous stimuli was determined in vivo by correlation analysis of different optical and spectroscopic readouts such as fluorescence lifetime (FLT). Furthermore, a new spectro-microscopic technique, fluorescence intensity decay shape analysis microscopy (FIDSAM), has been developed. FIDSAM is capable of imaging low-expressed fluorophore-tagged proteins at high spatial resolution and precludes the misinterpretation of autofluorescence artifacts. In addition, FIDSAM provides a very effective and sensitive tool on the basis of Förster resonance energy transfer (FRET) for the qualitative and quantitative determination of protein-protein interaction. Finally, we report on the quantitative analysis of the photosystem I and II (PSI/PSII) ratio in the chloroplasts of living Arabidopsis plants at room temperature, using high-resolution, spatially resolved fluorescence spectroscopy. With this technique, it was not only possible to measure PSI/PSII ratios, but also to demonstrate the differential competence of wild-type and carbohydrate-deficient plants to adapt the PSI/PSII ratio to different light conditions. In summary, the information content of standard microscopic images is extended by several dimensions by the use of spectro-microscopic approaches. Therefore, novel cell physiological and molecular topics can be addressed and valuable insights into molecular and subcellular processes can be obtained in living plants.

Emerging tools and technologies in watershed management

Treesearch

D. Phillip Guertin; Scott N. Miller; David C. Goodrich

2000-01-01

The field of watershed management is highly dependent on spatially distributed data. Over the past decade, significant advances have been made toward the capture, storage, and use of spatial data. Emerging tools and technologies hold great promise for improving the scientific understanding of watershed processes and are already revolutionizing watershed research....

Assessment of a Bayesian Belief Network-GIS framework as a practical tool to support marine planning.

PubMed

Stelzenmüller, V; Lee, J; Garnacho, E; Rogers, S I

2010-10-01

For the UK continental shelf we developed a Bayesian Belief Network-GIS framework to visualise relationships between cumulative human pressures, sensitive marine landscapes and landscape vulnerability, to assess the consequences of potential marine planning objectives, and to map uncertainty-related changes in management measures. Results revealed that the spatial assessment of footprints and intensities of human activities had more influence on landscape vulnerabilities than the type of landscape sensitivity measure used. We addressed questions regarding consequences of potential planning targets, and necessary management measures with spatially-explicit assessment of their consequences. We conclude that the BN-GIS framework is a practical tool allowing for the visualisation of relationships, the spatial assessment of uncertainty related to spatial management scenarios, the engagement of different stakeholder views, and enables a quick update of new spatial data and relationships. Ultimately, such BN-GIS based tools can support the decision-making process used in adaptive marine management. Copyright © 2010 Elsevier Ltd. All rights reserved.

Correction of mid-spatial-frequency errors by smoothing in spin motion for CCOS

NASA Astrophysics Data System (ADS)

Zhang, Yizhong; Wei, Chaoyang; Shao, Jianda; Xu, Xueke; Liu, Shijie; Hu, Chen; Zhang, Haichao; Gu, Haojin

2015-08-01

Smoothing is a convenient and efficient way to correct mid-spatial-frequency errors. Quantifying the smoothing effect allows improvements in efficiency for finishing precision optics. A series experiments in spin motion are performed to study the smoothing effects about correcting mid-spatial-frequency errors. Some of them use a same pitch tool at different spinning speed, and others at a same spinning speed with different tools. Introduced and improved Shu's model to describe and compare the smoothing efficiency with different spinning speed and different tools. From the experimental results, the mid-spatial-frequency errors on the initial surface were nearly smoothed out after the process in spin motion and the number of smoothing times can be estimated by the model before the process. Meanwhile this method was also applied to smooth the aspherical component, which has an obvious mid-spatial-frequency error after Magnetorheological Finishing processing. As a result, a high precision aspheric optical component was obtained with PV=0.1λ and RMS=0.01λ.

Constructing Benchmark Databases and Protocols for Medical Image Analysis: Diabetic Retinopathy

PubMed Central

Kauppi, Tomi; Kämäräinen, Joni-Kristian; Kalesnykiene, Valentina; Sorri, Iiris; Uusitalo, Hannu; Kälviäinen, Heikki

2013-01-01

We address the performance evaluation practices for developing medical image analysis methods, in particular, how to establish and share databases of medical images with verified ground truth and solid evaluation protocols. Such databases support the development of better algorithms, execution of profound method comparisons, and, consequently, technology transfer from research laboratories to clinical practice. For this purpose, we propose a framework consisting of reusable methods and tools for the laborious task of constructing a benchmark database. We provide a software tool for medical image annotation helping to collect class label, spatial span, and expert's confidence on lesions and a method to appropriately combine the manual segmentations from multiple experts. The tool and all necessary functionality for method evaluation are provided as public software packages. As a case study, we utilized the framework and tools to establish the DiaRetDB1 V2.1 database for benchmarking diabetic retinopathy detection algorithms. The database contains a set of retinal images, ground truth based on information from multiple experts, and a baseline algorithm for the detection of retinopathy lesions. PMID:23956787

A Web-based environmental decision support system (WEDSS) for environmental planning and watershed management

NASA Astrophysics Data System (ADS)

Sugumaran, Ramanathan; Meyer, James C.; Davis, Jim

2004-10-01

Local governments often struggle to balance competing demands for residential, commercial and industrial development with imperatives to minimize environmental degradation. In order to effectively manage this development process on a sustainable basis, local planners and government agencies are increasingly seeking better tools and techniques. In this paper, we describe the development of a Web-Based Environmental Decision Support System (WEDSS), which helps to prioritize local watersheds in terms of environmental sensitivity using multiple criteria identified by planners and local government staff in the city of Columbia, and Boone County, Missouri. The development of the system involved three steps, the first was to establish the relevant environmental criteria and develop data layers for each criterion, then a spatial model was developed for analysis, and lastly a Web-based interface with analysis tools was developed using client-server technology. The WEDSS is an example of a way to run spatial models over the Web and represents a significant increase in capability over other WWW-based GIS applications that focus on database querying and map display. The WEDSS seeks to aid in the development of agreement regarding specific local areas deserving increased protection and the public policies to be pursued in minimizing the environmental impact of future development. The tool is also intended to assist ongoing public information and education efforts concerning watershed management and water quality issues for the City of Columbia, Missouri and adjacent developing areas within Boone County, Missouri.

Using spatial principles to optimize distributed computing for enabling the physical science discoveries

PubMed Central

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-01-01

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century. PMID:21444779

Using spatial principles to optimize distributed computing for enabling the physical science discoveries.

PubMed

Yang, Chaowei; Wu, Huayi; Huang, Qunying; Li, Zhenlong; Li, Jing

2011-04-05

Contemporary physical science studies rely on the effective analyses of geographically dispersed spatial data and simulations of physical phenomena. Single computers and generic high-end computing are not sufficient to process the data for complex physical science analysis and simulations, which can be successfully supported only through distributed computing, best optimized through the application of spatial principles. Spatial computing, the computing aspect of a spatial cyberinfrastructure, refers to a computing paradigm that utilizes spatial principles to optimize distributed computers to catalyze advancements in the physical sciences. Spatial principles govern the interactions between scientific parameters across space and time by providing the spatial connections and constraints to drive the progression of the phenomena. Therefore, spatial computing studies could better position us to leverage spatial principles in simulating physical phenomena and, by extension, advance the physical sciences. Using geospatial science as an example, this paper illustrates through three research examples how spatial computing could (i) enable data intensive science with efficient data/services search, access, and utilization, (ii) facilitate physical science studies with enabling high-performance computing capabilities, and (iii) empower scientists with multidimensional visualization tools to understand observations and simulations. The research examples demonstrate that spatial computing is of critical importance to design computing methods to catalyze physical science studies with better data access, phenomena simulation, and analytical visualization. We envision that spatial computing will become a core technology that drives fundamental physical science advancements in the 21st century.

Enabling Web-Based GIS Tools for Internet and Mobile Devices To Improve and Expand NASA Data Accessibility and Analysis Functionality for the Renewable Energy and Agricultural Applications

NASA Astrophysics Data System (ADS)

Ross, A.; Stackhouse, P. W.; Tisdale, B.; Tisdale, M.; Chandler, W.; Hoell, J. M., Jr.; Kusterer, J.

2014-12-01

The NASA Langley Research Center Science Directorate and Atmospheric Science Data Center have initiated a pilot program to utilize Geographic Information System (GIS) tools that enable, generate and store climatological averages using spatial queries and calculations in a spatial database resulting in greater accessibility of data for government agencies, industry and private sector individuals. The major objectives of this effort include the 1) Processing and reformulation of current data to be consistent with ESRI and openGIS tools, 2) Develop functions to improve capability and analysis that produce "on-the-fly" data products, extending these past the single location to regional and global scales. 3) Update the current web sites to enable both web-based and mobile application displays for optimization on mobile platforms, 4) Interact with user communities in government and industry to test formats and usage of optimization, and 5) develop a series of metrics that allow for monitoring of progressive performance. Significant project results will include the the development of Open Geospatial Consortium (OGC) compliant web services (WMS, WCS, WFS, WPS) that serve renewable energy and agricultural application products to users using GIS software and tools. Each data product and OGC service will be registered within ECHO, the Common Metadata Repository, the Geospatial Platform, and Data.gov to ensure the data are easily discoverable and provide data users with enhanced access to SSE data, parameters, services, and applications. This effort supports cross agency, cross organization, and interoperability of SSE data products and services by collaborating with DOI, NRCan, NREL, NCAR, and HOMER for requirements vetting and test bed users before making available to the wider public.

OpenMSI Arrayed Analysis Toolkit: Analyzing Spatially Defined Samples Using Mass Spectrometry Imaging

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

de Raad, Markus; de Rond, Tristan; Rübel, Oliver

Mass spectrometry imaging (MSI) has primarily been applied in localizing biomolecules within biological matrices. Although well-suited, the application of MSI for comparing thousands of spatially defined spotted samples has been limited. One reason for this is a lack of suitable and accessible data processing tools for the analysis of large arrayed MSI sample sets. In this paper, the OpenMSI Arrayed Analysis Toolkit (OMAAT) is a software package that addresses the challenges of analyzing spatially defined samples in MSI data sets. OMAAT is written in Python and is integrated with OpenMSI (http://openmsi.nersc.gov), a platform for storing, sharing, and analyzing MSI data.more » By using a web-based python notebook (Jupyter), OMAAT is accessible to anyone without programming experience yet allows experienced users to leverage all features. OMAAT was evaluated by analyzing an MSI data set of a high-throughput glycoside hydrolase activity screen comprising 384 samples arrayed onto a NIMS surface at a 450 μm spacing, decreasing analysis time >100-fold while maintaining robust spot-finding. The utility of OMAAT was demonstrated for screening metabolic activities of different sized soil particles, including hydrolysis of sugars, revealing a pattern of size dependent activities. Finally, these results introduce OMAAT as an effective toolkit for analyzing spatially defined samples in MSI. OMAAT runs on all major operating systems, and the source code can be obtained from the following GitHub repository: https://github.com/biorack/omaat.« less

TASI: A software tool for spatial-temporal quantification of tumor spheroid dynamics.

PubMed

Hou, Yue; Konen, Jessica; Brat, Daniel J; Marcus, Adam I; Cooper, Lee A D

2018-05-08

Spheroid cultures derived from explanted cancer specimens are an increasingly utilized resource for studying complex biological processes like tumor cell invasion and metastasis, representing an important bridge between the simplicity and practicality of 2-dimensional monolayer cultures and the complexity and realism of in vivo animal models. Temporal imaging of spheroids can capture the dynamics of cell behaviors and microenvironments, and when combined with quantitative image analysis methods, enables deep interrogation of biological mechanisms. This paper presents a comprehensive open-source software framework for Temporal Analysis of Spheroid Imaging (TASI) that allows investigators to objectively characterize spheroid growth and invasion dynamics. TASI performs spatiotemporal segmentation of spheroid cultures, extraction of features describing spheroid morpho-phenotypes, mathematical modeling of spheroid dynamics, and statistical comparisons of experimental conditions. We demonstrate the utility of this tool in an analysis of non-small cell lung cancer spheroids that exhibit variability in metastatic and proliferative behaviors.

Open source tools for the information theoretic analysis of neural data.

PubMed

Ince, Robin A A; Mazzoni, Alberto; Petersen, Rasmus S; Panzeri, Stefano

2010-01-01

The recent and rapid development of open source software tools for the analysis of neurophysiological datasets consisting of simultaneous multiple recordings of spikes, field potentials and other neural signals holds the promise for a significant advance in the standardization, transparency, quality, reproducibility and variety of techniques used to analyze neurophysiological data and for the integration of information obtained at different spatial and temporal scales. In this review we focus on recent advances in open source toolboxes for the information theoretic analysis of neural responses. We also present examples of their use to investigate the role of spike timing precision, correlations across neurons, and field potential fluctuations in the encoding of sensory information. These information toolboxes, available both in MATLAB and Python programming environments, hold the potential to enlarge the domain of application of information theory to neuroscience and to lead to new discoveries about how neurons encode and transmit information.

"EWS Matrix" and "EWG Matrix": "De-sign for All" tools referred to the development of a enabling communication system for public spaces.

PubMed

Di Bucchianico, Giuseppe; Camplone, Stefania; Picciani, Stefano; Vallese, Valeria

2012-01-01

The widespread sense of spatial disorientation that can be experienced in many public places (buildings and open spaces),generally depends on a design approach that doesn't take into account both the "communication skills" of the different parts of the spatial organization, both the variability of people and their ways of interacting with environments, orienteering themselves. Nevertheless, "not find the way" often has some obvious practical costs (loss of time, failure to achieve a target) and some more intangible, but no less important, emotional costs. That's why the design of signage systems must take into account both the specificities of places and the extreme variability of its users. The paper presents the results of a study on this specific issue. In particular, the study focuses on the description of some tools useful for the analysis and design of a signage system that is truly "for All".

A lithospheric magnetic field model derived from the Swarm satellite magnetic field measurements

NASA Astrophysics Data System (ADS)

Hulot, G.; Thebault, E.; Vigneron, P.

2015-12-01

The Swarm constellation of satellites was launched in November 2013 and has since then delivered high quality scalar and vector magnetic field measurements. A consortium of several research institutions was selected by the European Space Agency (ESA) to provide a number of scientific products which will be made available to the scientific community. Within this framework, specific tools were tailor-made to better extract the magnetic signal emanating from Earth's the lithospheric. These tools rely on the scalar gradient measured by the lower pair of Swarm satellites and rely on a regional modeling scheme that is more sensitive to small spatial scales and weak signals than the standard spherical harmonic modeling. In this presentation, we report on various activities related to data analysis and processing. We assess the efficiency of this dedicated chain for modeling the lithospheric magnetic field using more than one year of measurements, and finally discuss refinements that are continuously implemented in order to further improve the robustness and the spatial resolution of the lithospheric field model.

Spatiotemporal analysis of air conditions as a tool for the environmental management of a show cave (Cueva del Agua, Spain)

NASA Astrophysics Data System (ADS)

Fernandez-Cortes, A.; Calaforra, J. M.; Sanchez-Martos, F.

We recorded the air temperature and carbon dioxide concentration within the Cueva del Agua, a cave in Spain, under natural conditions prior to the cave being opened to tourists. Geostatistical tools are useful techniques for characterizing microclimate parameters with the aim of adopting measures to ensure the conservation and sound environmental management of tourist caves. We modelled the spatial distribution of these microclimatic parameters over an annual cycle using iterative residual kriging, revealing the stratification of air related to the cave's topography. Replenishment of the cave air is activated by convective circulation that accompanies the development of inversions in the thermal gradient of the air. Comparison of the spatial distribution of each microclimatic parameter over time enables us to characterize the exchange of air between the cave interior and the outside, as well as identify potential areas that could be opened to tourists and determine suitable visiting schedules.

Platform for Quantitative Evaluation of Spatial Intratumoral Heterogeneity in Multiplexed Fluorescence Images.

PubMed

Spagnolo, Daniel M; Al-Kofahi, Yousef; Zhu, Peihong; Lezon, Timothy R; Gough, Albert; Stern, Andrew M; Lee, Adrian V; Ginty, Fiona; Sarachan, Brion; Taylor, D Lansing; Chennubhotla, S Chakra

2017-11-01

We introduce THRIVE (Tumor Heterogeneity Research Interactive Visualization Environment), an open-source tool developed to assist cancer researchers in interactive hypothesis testing. The focus of this tool is to quantify spatial intratumoral heterogeneity (ITH), and the interactions between different cell phenotypes and noncellular constituents. Specifically, we foresee applications in phenotyping cells within tumor microenvironments, recognizing tumor boundaries, identifying degrees of immune infiltration and epithelial/stromal separation, and identification of heterotypic signaling networks underlying microdomains. The THRIVE platform provides an integrated workflow for analyzing whole-slide immunofluorescence images and tissue microarrays, including algorithms for segmentation, quantification, and heterogeneity analysis. THRIVE promotes flexible deployment, a maintainable code base using open-source libraries, and an extensible framework for customizing algorithms with ease. THRIVE was designed with highly multiplexed immunofluorescence images in mind, and, by providing a platform to efficiently analyze high-dimensional immunofluorescence signals, we hope to advance these data toward mainstream adoption in cancer research. Cancer Res; 77(21); e71-74. ©2017 AACR . ©2017 American Association for Cancer Research.

Harnessing cell-to-cell variations to probe bacterial structure and biophysics

NASA Astrophysics Data System (ADS)

Cass, Julie A.

Advances in microscopy and biotechnology have given us novel insights into cellular biology and physics. While bacteria were long considered to be relatively unstructured, the development of fluorescence microscopy techniques, and spatially and temporally resolved high-throughput quantitative studies, have uncovered that the bacterial cell is highly organized, and its structure rigorously maintained. In this thesis I will describe our gateTool software, designed to harness cell-to-cell variations to probe bacterial structure, and discuss two exciting aspects of structure that we have employed gateTool to investigate: (i) chromosome organization and the cellular mechanisms for controlling DNA dynamics, and (ii) the study of cell wall synthesis, and how the genes in the synthesis pathway impact cellular shape. In the first project, we develop a spatial and temporal mapping of cell-cycle-dependent chromosomal organization, and use this quantitative map to discover that chromosomal loci segregate from midcell with universal dynamics. In the second project, I describe preliminary time- lapse and snapshot imaging analysis suggesting phentoypical coherence across peptidoglycan synthesis pathways.

Magnetic resonance imaging in laboratory petrophysical core analysis

NASA Astrophysics Data System (ADS)

Mitchell, J.; Chandrasekera, T. C.; Holland, D. J.; Gladden, L. F.; Fordham, E. J.

2013-05-01

Magnetic resonance imaging (MRI) is a well-known technique in medical diagnosis and materials science. In the more specialized arena of laboratory-scale petrophysical rock core analysis, the role of MRI has undergone a substantial change in focus over the last three decades. Initially, alongside the continual drive to exploit higher magnetic field strengths in MRI applications for medicine and chemistry, the same trend was followed in core analysis. However, the spatial resolution achievable in heterogeneous porous media is inherently limited due to the magnetic susceptibility contrast between solid and fluid. As a result, imaging resolution at the length-scale of typical pore diameters is not practical and so MRI of core-plugs has often been viewed as an inappropriate use of expensive magnetic resonance facilities. Recently, there has been a paradigm shift in the use of MRI in laboratory-scale core analysis. The focus is now on acquiring data in the laboratory that are directly comparable to data obtained from magnetic resonance well-logging tools (i.e., a common physics of measurement). To maintain consistency with well-logging instrumentation, it is desirable to measure distributions of transverse (T2) relaxation time-the industry-standard metric in well-logging-at the laboratory-scale. These T2 distributions can be spatially resolved over the length of a core-plug. The use of low-field magnets in the laboratory environment is optimal for core analysis not only because the magnetic field strength is closer to that of well-logging tools, but also because the magnetic susceptibility contrast is minimized, allowing the acquisition of quantitative image voxel (or pixel) intensities that are directly scalable to liquid volume. Beyond simple determination of macroscopic rock heterogeneity, it is possible to utilize the spatial resolution for monitoring forced displacement of oil by water or chemical agents, determining capillary pressure curves, and estimating wettability. The history of MRI in petrophysics is reviewed and future directions considered, including advanced data processing techniques such as compressed sensing reconstruction and Bayesian inference analysis of under-sampled data. Although this review focuses on rock core analysis, the techniques described are applicable in a wider context to porous media in general, such as cements, soils, ceramics, and catalytic materials.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Effects of a GIS Course on Self-Assessment of Spatial Habits of Mind (SHOM)

ERIC Educational Resources Information Center

Kim, Minsung; Bednarz, Robert

2013-01-01

This study identified five subdimensions of spatial habits of mind--pattern recognition, spatial description, visualization, spatial concept use, and spatial tool use--and created an inventory to measure them. In addition, the effects of GIS learning on spatial habits of mind were investigated. Pre- and post-tests were conducted at the beginning…

Predictive Spatial Analysis of Marine Mammal Habitats

DTIC Science & Technology

2010-01-01

Therefore, it would be desirable to focus on biological components of their habitat to describe their patterns of distribution and abundance . For...difficult (and often impossible) to determine prey abundance and distribution in the ocean, even with commercially important species. We currently do...not have the tools to determine the distribution and abundance of these prey species at scales that are relevant to either marine mammals or the

Next-generation technologies for spatial proteomics: Integrating ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR imaging mass spectrometry for protein analysis.

PubMed

Spraggins, Jeffrey M; Rizzo, David G; Moore, Jessica L; Noto, Michael J; Skaar, Eric P; Caprioli, Richard M

2016-06-01

MALDI imaging mass spectrometry is a powerful analytical tool enabling the visualization of biomolecules in tissue. However, there are unique challenges associated with protein imaging experiments including the need for higher spatial resolution capabilities, improved image acquisition rates, and better molecular specificity. Here we demonstrate the capabilities of ultra-high speed MALDI-TOF and high mass resolution MALDI FTICR IMS platforms as they relate to these challenges. High spatial resolution MALDI-TOF protein images of rat brain tissue and cystic fibrosis lung tissue were acquired at image acquisition rates >25 pixels/s. Structures as small as 50 μm were spatially resolved and proteins associated with host immune response were observed in cystic fibrosis lung tissue. Ultra-high speed MALDI-TOF enables unique applications including megapixel molecular imaging as demonstrated for lipid analysis of cystic fibrosis lung tissue. Additionally, imaging experiments using MALDI FTICR IMS were shown to produce data with high mass accuracy (<5 ppm) and resolving power (∼75 000 at m/z 5000) for proteins up to ∼20 kDa. Analysis of clear cell renal cell carcinoma using MALDI FTICR IMS identified specific proteins localized to healthy tissue regions, within the tumor, and also in areas of increased vascularization around the tumor. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Development of Semi-distributed ecohydrological model in the Rio Grande De Manati River Basin, Puerto Rico

NASA Astrophysics Data System (ADS)

Setegn, S. G.; Ortiz, J.; Melendez, J.; Barreto, M.; Torres-Perez, J. L.; Guild, L. S.

2015-12-01

There are limited studies in Puerto Rico that shows the water resources availability and variability with respect to changing climates and land use. The main goal of the HICE-PR (Human Impacts to Coastal Ecosystems in Puerto Rico (HICE-PR): the Río Loco Watershed (southwest coast PR) project which was funded by NASA is to evaluate the impacts of land use/land cover changes on the quality and extent of coastal and marine ecosystems (CMEs) in two priority watersheds in Puerto Rico (Manatí and Guánica).The main objective of this study is to set up a physically based spatially distributed hydrological model, Soil and Water Assessment Tool (SWAT) for the analysis of hydrological processes in the Rio Grande de Manati river basin. SWAT (soil and water assessment tool) is a spatially distributed watershed model developed to predict the impact of land management practices on water, sediment and agricultural chemical yields in large complex watersheds. For efficient use of distributed models for hydrological and scenario analysis, it is important that these models pass through a careful calibration and uncertainty analysis. The model was calibrated and validated using Sequential Uncertainty Fitting (SUFI-2) calibration and uncertainty analysis algorithms. The model evaluation statistics for streamflows prediction shows that there is a good agreement between the measured and simulated flows that was verified by coefficients of determination and Nash Sutcliffe efficiency greater than 0.5. Keywords: Hydrological Modeling; SWAT; SUFI-2; Rio Grande De Manati; Puerto Rico

Analysis of risk factors for T. brucei rhodesiense sleeping sickness within villages in south-east Uganda

PubMed Central

Zoller, Thomas; Fèvre, Eric M; Welburn, Susan C; Odiit, Martin; Coleman, Paul G

2008-01-01

Background Sleeping sickness (HAT) caused by T.b. rhodesiense is a major veterinary and human public health problem in Uganda. Previous studies have investigated spatial risk factors for T.b. rhodesiense at large geographic scales, but none have properly investigated such risk factors at small scales, i.e. within affected villages. In the present work, we use a case-control methodology to analyse both behavioural and spatial risk factors for HAT in an endemic area. Methods The present study investigates behavioural and occupational risk factors for infection with HAT within villages using a questionnaire-based case-control study conducted in 17 villages endemic for HAT in SE Uganda, and spatial risk factors in 4 high risk villages. For the spatial analysis, the location of homesteads with one or more cases of HAT up to three years prior to the beginning of the study was compared to all non-case homesteads. Analysing spatial associations with respect to irregularly shaped geographical objects required the development of a new approach to geographical analysis in combination with a logistic regression model. Results The study was able to identify, among other behavioural risk factors, having a family member with a history of HAT (p = 0.001) as well as proximity of a homestead to a nearby wetland area (p < 0.001) as strong risk factors for infection. The novel method of analysing complex spatial interactions used in the study can be applied to a range of other diseases. Conclusion Spatial risk factors for HAT are maintained across geographical scales; this consistency is useful in the design of decision support tools for intervention and prevention of the disease. Familial aggregation of cases was confirmed for T. b. rhodesiense HAT in the study and probably results from shared behavioural and spatial risk factors amongmembers of a household. PMID:18590541

Search Analytics: Automated Learning, Analysis, and Search with Open Source

NASA Astrophysics Data System (ADS)

Hundman, K.; Mattmann, C. A.; Hyon, J.; Ramirez, P.

2016-12-01

The sheer volume of unstructured scientific data makes comprehensive human analysis impossible, resulting in missed opportunities to identify relationships, trends, gaps, and outliers. As the open source community continues to grow, tools like Apache Tika, Apache Solr, Stanford's DeepDive, and Data-Driven Documents (D3) can help address this challenge. With a focus on journal publications and conference abstracts often in the form of PDF and Microsoft Office documents, we've initiated an exploratory NASA Advanced Concepts project aiming to use the aforementioned open source text analytics tools to build a data-driven justification for the HyspIRI Decadal Survey mission. We call this capability Search Analytics, and it fuses and augments these open source tools to enable the automatic discovery and extraction of salient information. In the case of HyspIRI, a hyperspectral infrared imager mission, key findings resulted from the extractions and visualizations of relationships from thousands of unstructured scientific documents. The relationships include links between satellites (e.g. Landsat 8), domain-specific measurements (e.g. spectral coverage) and subjects (e.g. invasive species). Using the above open source tools, Search Analytics mined and characterized a corpus of information that would be infeasible for a human to process. More broadly, Search Analytics offers insights into various scientific and commercial applications enabled through missions and instrumentation with specific technical capabilities. For example, the following phrases were extracted in close proximity within a publication: "In this study, hyperspectral images…with high spatial resolution (1 m) were analyzed to detect cutleaf teasel in two areas. …Classification of cutleaf teasel reached a users accuracy of 82 to 84%." Without reading a single paper we can use Search Analytics to automatically identify that a 1 m spatial resolution provides a cutleaf teasel detection users accuracy of 82-84%, which could have tangible, direct downstream implications for crop protection. Automatically assimilating this information expedites and supplements human analysis, and, ultimately, Search Analytics and its foundation of open source tools will result in more efficient scientific investment and research.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Linking climate change and fish conservation efforts using spatially explicit decision support tools

Treesearch

Douglas P. Peterson; Seth J. Wenger; Bruce E. Rieman; Daniel J. Isaak

2013-01-01

Fisheries professionals are increasingly tasked with incorporating climate change projections into their decisions. Here we demonstrate how a structured decision framework, coupled with analytical tools and spatial data sets, can help integrate climate and biological information to evaluate management alternatives. We present examples that link downscaled climate...

Integrated landscape/hydrologic modeling tool for semiarid watersheds

Treesearch

Mariano Hernandez; Scott N. Miller

2000-01-01

An integrated hydrologic modeling/watershed assessment tool is being developed to aid in determining the susceptibility of semiarid landscapes to natural and human-induced changes across a range of scales. Watershed processes are by definition spatially distributed and are highly variable through time, and this approach is designed to account for their spatial and...

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

PubMed Central

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

2011-01-01

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

Multi-Spacecraft Analysis with Generic Visualization Tools

NASA Astrophysics Data System (ADS)

Mukherjee, J.; Vela, L.; Gonzalez, C.; Jeffers, S.

2010-12-01

To handle the needs of scientists today and in the future, software tools are going to have to take better advantage of the currently available hardware. Specifically, computing power, memory, and disk space have become cheaper, while bandwidth has become more expensive due to the explosion of online applications. To overcome these limitations, we have enhanced our Southwest Data Display and Analysis System (SDDAS) to take better advantage of the hardware by utilizing threads and data caching. Furthermore, the system was enhanced to support a framework for adding data formats and data visualization methods without costly rewrites. Visualization tools can speed analysis of many common scientific tasks and we will present a suite of tools that encompass the entire process of retrieving data from multiple data stores to common visualizations of the data. The goals for the end user are ease of use and interactivity with the data and the resulting plots. The data can be simultaneously plotted in a variety of formats and/or time and spatial resolutions. The software will allow one to slice and separate data to achieve other visualizations. Furthermore, one can interact with the data using the GUI or through an embedded language based on the Lua scripting language. The data presented will be primarily from the Cluster and Mars Express missions; however, the tools are data type agnostic and can be used for virtually any type of data.

Spatial landscape model to characterize biological diversity using R statistical computing environment.

PubMed

Singh, Hariom; Garg, R D; Karnatak, Harish C; Roy, Arijit

2018-01-15

Due to urbanization and population growth, the degradation of natural forests and associated biodiversity are now widely recognized as a global environmental concern. Hence, there is an urgent need for rapid assessment and monitoring of biodiversity on priority using state-of-art tools and technologies. The main purpose of this research article is to develop and implement a new methodological approach to characterize biological diversity using spatial model developed during the study viz. Spatial Biodiversity Model (SBM). The developed model is scale, resolution and location independent solution for spatial biodiversity richness modelling. The platform-independent computation model is based on parallel computation. The biodiversity model based on open-source software has been implemented on R statistical computing platform. It provides information on high disturbance and high biological richness areas through different landscape indices and site specific information (e.g. forest fragmentation (FR), disturbance index (DI) etc.). The model has been developed based on the case study of Indian landscape; however it can be implemented in any part of the world. As a case study, SBM has been tested for Uttarakhand state in India. Inputs for landscape ecology are derived through multi-criteria decision making (MCDM) techniques in an interactive command line environment. MCDM with sensitivity analysis in spatial domain has been carried out to illustrate the model stability and robustness. Furthermore, spatial regression analysis has been made for the validation of the output. Copyright © 2017 Elsevier Ltd. All rights reserved.

The spatial epidemiology of trauma: the potential of geographic information science to organize data and reveal patterns of injury and services

PubMed Central

Schuurman, Nadine; Hameed, S. Morad; Fiedler, Robert; Bell, Nathaniel; Simons, Richard K.

2008-01-01

Despite important advances in the prevention and treatment of trauma, preventable injuries continue to impact the lives of millions of people. Motor vehicle collisions and violence claim close to 3 million lives each year worldwide. Public health agencies have promoted the need for systematic and ongoing surveillance as a foundation for successful injury control. Surveillance has been used to quantify the incidence of injury for the prioritization of further research, monitor trends over time, identify new injury patterns, and plan and evaluate prevention and intervention efforts. Advances in capability to handle spatial data and substantial increases in computing power have positioned geographic information science (GIS) as a potentially important tool for health surveillance and the spatial organization of health care, and for informing prevention and acute care interventions. Two themes emerge in the trauma literature with respect to GIS theory and techniques: identifying determinants associated with the risk of trauma to guide injury prevention efforts and evaluating the spatial organization and accessibility of acute trauma care systems. We review the current literature on trauma and GIS research and provide examples of the importance of accounting for spatial scale when using spatial analysis for surveillance. The examples illustrate the effect of scale on incident analysis, the geographic variation of major injury across British Columbia's health service delivery areas (HSDAs) and the rates of variation of injury within individual HSDAs. PMID:18841227

A Powerful, Cost Effective, Web Based Engineering Solution Supporting Conjunction Detection and Visual Analysis

NASA Astrophysics Data System (ADS)

Novak, Daniel M.; Biamonti, Davide; Gross, Jeremy; Milnes, Martin

2013-08-01

An innovative and visually appealing tool is presented for efficient all-vs-all conjunction analysis on a large catalogue of objects. The conjunction detection uses a nearest neighbour search algorithm, based on spatial binning and identification of pairs of objects in adjacent bins. This results in the fastest all vs all filtering the authors are aware of. The tool is constructed on a server-client architecture, where the server broadcasts to the client the conjunction data and ephemerides, while the client supports the user interface through a modern browser, without plug-in. In order to make the tool flexible and maintainable, Java software technologies were used on the server side, including Spring, Camel, ActiveMQ and CometD. The user interface and visualisation are based on the latest web technologies: HTML5, WebGL, THREE.js. Importance has been given on the ergonomics and visual appeal of the software. In fact certain design concepts have been borrowed from the gaming industry.

Sonification Prototype for Space Physics

NASA Astrophysics Data System (ADS)

Candey, R. M.; Schertenleib, A. M.; Diaz Merced, W. L.

2005-12-01

As an alternative and adjunct to visual displays, auditory exploration of data via sonification (data controlled sound) and audification (audible playback of data samples) is promising for complex or rapidly/temporally changing visualizations, for data exploration of large datasets (particularly multi-dimensional datasets), and for exploring datasets in frequency rather than spatial dimensions (see also International Conferences on Auditory Display ). Besides improving data exploration and analysis for most researchers, the use of sound is especially valuable as an assistive technology for visually-impaired people and can make science and math more exciting for high school and college students. Only recently have the hardware and software come together to make a cross-platform open-source sonification tool feasible. We have developed a prototype sonification data analysis tool using the JavaSound API and NASA GSFC's ViSBARD software . Wanda Diaz Merced, a blind astrophysicist from Puerto Rico, is instrumental in advising on and testing the tool.

Balancing geo-privacy and spatial patterns in epidemiological studies.

PubMed

Chen, Chien-Chou; Chuang, Jen-Hsiang; Wang, Da-Wei; Wang, Chien-Min; Lin, Bo-Cheng; Chan, Ta-Chien

2017-11-08

To balance the protection of geo-privacy and the accuracy of spatial patterns, we developed a geo-spatial tool (GeoMasker) intended to mask the residential locations of patients or cases in a geographic information system (GIS). To elucidate the effects of geo-masking parameters, we applied 2010 dengue epidemic data from Taiwan testing the tool's performance in an empirical situation. The similarity of pre- and post-spatial patterns was measured by D statistics under a 95% confidence interval. In the empirical study, different magnitudes of anonymisation (estimated Kanonymity ≥10 and 100) were achieved and different degrees of agreement on the pre- and post-patterns were evaluated. The application is beneficial for public health workers and researchers when processing data with individuals' spatial information.

Measuring Spatial Dependence for Infectious Disease Epidemiology

PubMed Central

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

2016-01-01

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

Hyperspectral analysis of cultural heritage artifacts: pigment material diversity in the Gough Map of Britain

NASA Astrophysics Data System (ADS)

Bai, Di; Messinger, David W.; Howell, David

2017-08-01

The Gough Map, one of the earliest surviving maps of Britain, was created and extensively revised over the 15th century. In 2015, the map was imaged using a hyperspectral imaging system while in the collection at the Bodleian Library, Oxford University. The goal of the collection of the hyperspectral image (HSI) of the Gough Map was to address questions such as enhancement of faded text for reading and analysis of the pigments used during its creation and revision. In particular, pigment analysis of the Gough Map will help historians understand the material diversity of its composition and potentially the timeline of, and methods used in, the creation and revision of the map. Multiple analysis methods are presented to analyze a particular pigment in the Gough Map with an emphasis on understanding the within-material diversity, i.e., the number and spatial layout of distinct red pigments. One approach for understanding the number of distinct materials in a scene (i.e., endmember selection and dimensionality estimation) is the Gram matrix approach. Here, this method is used to study the within-material differences of pigments in the map with common visual color. The application is a pigment analysis tool that extracts visually common pixels (here, the red pigments) from the Gough Map and estimates the material diversity of the pixels. Results show that the Gough Map is composed of at least five kinds of dominant red pigments with a particular spatial pattern. This research provides a useful tool for historical geographers and cartographic historians to analyze the material diversity of HSI of cultural heritage artifacts.

Methods for Data-based Delineation of Spatial Regions

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

Wilson, John E.

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

Spatial access to residential care resources in Beijing, China

PubMed Central

2012-01-01

Background As the population is ageing rapidly in Beijing, the residential care sector is in a fast expansion process with the support of the municipal government. Understanding spatial accessibility to residential care resources by older people supports the need for rational allocation of care resources in future planning. Methods Based on population data and data on residential care resources, this study uses two Geographic Information System (GIS) based methods – shortest path analysis and a two-step floating catchment area (2SFCA) method to analyse spatial accessibility to residential care resources. Results Spatial accessibility varies as the methods and considered factors change. When only time distance is considered, residential care resources are more accessible in the central city than in suburban and exurban areas. If care resources are considered in addition to time distance, spatial accessibility is relatively poor in the central city compared to the northeast to southeast side of the suburban and exurban areas. The resources in the northwest to southwest side of the city are the least accessible, even though several hotspots of residential care resources are located in these areas. Conclusions For policy making, it may require combining various methods for a comprehensive analysis. The methods used in this study provide tools for identifying underserved areas in order to improve equity in access to and efficiency in allocation of residential care resources in future planning. PMID:22877360

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

Catching the right wave: evaluating wave energy resources and potential compatibility with existing marine and coastal uses.

PubMed

Kim, Choong-Ki; Toft, Jodie E; Papenfus, Michael; Verutes, Gregory; Guerry, Anne D; Ruckelshaus, Marry H; Arkema, Katie K; Guannel, Gregory; Wood, Spencer A; Bernhardt, Joanna R; Tallis, Heather; Plummer, Mark L; Halpern, Benjamin S; Pinsky, Malin L; Beck, Michael W; Chan, Francis; Chan, Kai M A; Levin, Phil S; Polasky, Stephen

2012-01-01

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses.

The contribution of multidimensional spatial analysis to a waste management policy: implementation of the ELECTRE method for characterizing transfer centers in the region of Oran

NASA Astrophysics Data System (ADS)

Saidi, A.; Trache, M. A.; Khelfi, M. F.

2016-08-01

The social and economic activity steadily growing in our cities creates a significant waste production in constantly evolving. The management of this waste is problematic because it is the center of many issues and interests. Indeed, any action or decision to the collection, transportation, treatment and disposal of waste should be considered in the economic, social, political and especially environmental aspect. A global Geomatic solution requires implementing a GIS with powerful multidimensional spatial analysis tools that support really waste management problem. Algeria has adopted a solution of waste landfill for all urban cities. In the Oran region, it exists three Centers Controlled landfill (CET) which the most important is that of Hassi-Bounif. This center currently meeting the needs of the region is unsustainable solution at the long-term because of its rapid saturation and its geographic location, which is still far from city centers (20-30 km) implying a negative impact on the vehicle park collecting such frequent breakdowns, the rapid degradation, slow delivery time and especially the high cost of the maintenance operation. This phenomenon is aggravated by the absence of real and actual initiatives targeting the recycling and recovery of waste, which makes the CET an endpoint for all types of waste. We present in this study, the use of the ELECTRE method (Multicriteria Analysis) integrated into a GIS to characterize the impact of the implementation of transfers centers at Oran region. The results of this study will accentuate the advantages of the activation of waste warehouse closer to the city, and relieving considerably the volume of transfer towards CET. The objective of our presentation is to show the leading role of the new Geomatics tools and the multidimensional spatial analysis in the apprehension of an environmental problem such the waste management and more generally in the urban management.

Catching the Right Wave: Evaluating Wave Energy Resources and Potential Compatibility with Existing Marine and Coastal Uses

PubMed Central

Kim, Choong-Ki; Toft, Jodie E.; Papenfus, Michael; Verutes, Gregory; Guerry, Anne D.; Ruckelshaus, Marry H.; Arkema, Katie K.; Guannel, Gregory; Wood, Spencer A.; Bernhardt, Joanna R.; Tallis, Heather; Plummer, Mark L.; Halpern, Benjamin S.; Pinsky, Malin L.; Beck, Michael W.; Chan, Francis; Chan, Kai M. A.; Levin, Phil S.; Polasky, Stephen

2012-01-01

Many hope that ocean waves will be a source for clean, safe, reliable and affordable energy, yet wave energy conversion facilities may affect marine ecosystems through a variety of mechanisms, including competition with other human uses. We developed a decision-support tool to assist siting wave energy facilities, which allows the user to balance the need for profitability of the facilities with the need to minimize conflicts with other ocean uses. Our wave energy model quantifies harvestable wave energy and evaluates the net present value (NPV) of a wave energy facility based on a capital investment analysis. The model has a flexible framework and can be easily applied to wave energy projects at local, regional, and global scales. We applied the model and compatibility analysis on the west coast of Vancouver Island, British Columbia, Canada to provide information for ongoing marine spatial planning, including potential wave energy projects. In particular, we conducted a spatial overlap analysis with a variety of existing uses and ecological characteristics, and a quantitative compatibility analysis with commercial fisheries data. We found that wave power and harvestable wave energy gradually increase offshore as wave conditions intensify. However, areas with high economic potential for wave energy facilities were closer to cable landing points because of the cost of bringing energy ashore and thus in nearshore areas that support a number of different human uses. We show that the maximum combined economic benefit from wave energy and other uses is likely to be realized if wave energy facilities are sited in areas that maximize wave energy NPV and minimize conflict with existing ocean uses. Our tools will help decision-makers explore alternative locations for wave energy facilities by mapping expected wave energy NPV and helping to identify sites that provide maximal returns yet avoid spatial competition with existing ocean uses. PMID:23144824

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 geostatistics-informed hierarchical sensitivity analysis method for complex groundwater flow and transport modeling

NASA Astrophysics Data System (ADS)

Dai, Heng; Chen, Xingyuan; Ye, Ming; Song, Xuehang; Zachara, John M.

2017-05-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study, we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multilayer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially distributed input variables.

A Geostatistics-Informed Hierarchical Sensitivity Analysis Method for Complex Groundwater Flow and Transport Modeling

NASA Astrophysics Data System (ADS)

Dai, H.; Chen, X.; Ye, M.; Song, X.; Zachara, J. M.

2017-12-01

Sensitivity analysis is an important tool for development and improvement of mathematical models, especially for complex systems with a high dimension of spatially correlated parameters. Variance-based global sensitivity analysis has gained popularity because it can quantify the relative contribution of uncertainty from different sources. However, its computational cost increases dramatically with the complexity of the considered model and the dimension of model parameters. In this study we developed a new sensitivity analysis method that integrates the concept of variance-based method with a hierarchical uncertainty quantification framework. Different uncertain inputs are grouped and organized into a multi-layer framework based on their characteristics and dependency relationships to reduce the dimensionality of the sensitivity analysis. A set of new sensitivity indices are defined for the grouped inputs using the variance decomposition method. Using this methodology, we identified the most important uncertainty source for a dynamic groundwater flow and solute transport model at the Department of Energy (DOE) Hanford site. The results indicate that boundary conditions and permeability field contribute the most uncertainty to the simulated head field and tracer plume, respectively. The relative contribution from each source varied spatially and temporally. By using a geostatistical approach to reduce the number of realizations needed for the sensitivity analysis, the computational cost of implementing the developed method was reduced to a practically manageable level. The developed sensitivity analysis method is generally applicable to a wide range of hydrologic and environmental problems that deal with high-dimensional spatially-distributed input variables.

Development of a Geometric Spatial Visualization Tool

ERIC Educational Resources Information Center

Ganesh, Bibi; Wilhelm, Jennifer; Sherrod, Sonya

2009-01-01

This paper documents the development of the Geometric Spatial Assessment. We detail the development of this instrument which was designed to identify middle school students' strategies and advancement in understanding of four geometric concept domains (geometric spatial visualization, spatial projection, cardinal directions, and periodic patterns)…

A Study on Re-entry Predictions of Uncontrolled Space Objects for Space Situational Awareness

NASA Astrophysics Data System (ADS)

Choi, Eun-Jung; Cho, Sungki; Lee, Deok-Jin; Kim, Siwoo; Jo, Jung Hyun

2017-12-01

The key risk analysis technologies for the re-entry of space objects into Earth’s atmosphere are divided into four categories: cataloguing and databases of the re-entry of space objects, lifetime and re-entry trajectory predictions, break-up models after re-entry and multiple debris distribution predictions, and ground impact probability models. In this study, we focused on re- entry prediction, including orbital lifetime assessments, for space situational awareness systems. Re-entry predictions are very difficult and are affected by various sources of uncertainty. In particular, during uncontrolled re-entry, large spacecraft may break into several pieces of debris, and the surviving fragments can be a significant hazard for persons and properties on the ground. In recent years, specific methods and procedures have been developed to provide clear information for predicting and analyzing the re-entry of space objects and for ground-risk assessments. Representative tools include object reentry survival analysis tool (ORSAT) and debris assessment software (DAS) developed by National Aeronautics and Space Administration (NASA), spacecraft atmospheric re-entry and aerothermal break-up (SCARAB) and debris risk assessment and mitigation analysis (DRAMA) developed by European Space Agency (ESA), and semi-analytic tool for end of life analysis (STELA) developed by Centre National d’Etudes Spatiales (CNES). In this study, various surveys of existing re-entry space objects are reviewed, and an efficient re-entry prediction technique is suggested based on STELA, the life-cycle analysis tool for satellites, and DRAMA, a re-entry analysis tool. To verify the proposed method, the re-entry of the Tiangong-1 Space Lab, which is expected to re-enter Earth’s atmosphere shortly, was simulated. Eventually, these results will provide a basis for space situational awareness risk analyses of the re-entry of space objects.

Detection of particle flow patterns in tumor by directional spatial frequency analysis

NASA Astrophysics Data System (ADS)

Russell, Stewart; Camara, Hawa; Shi, Lingyan; Hoopes, P. Jack; Kaufman, Peter; Pogue, Brian; Alfano, Robert

2016-04-01

Drug delivery to tumors is well known to be chaotic and limited, partly from dysfunctional vasculature, but also because of microscopic regional variations in composition. Modeling the of transport of nanoparticle therapeutics, therefore must include not only a description of vascular permeability, but also of the movement of the drug as suspended in tumor interstitial fluid (TIF) once it leaves the blood vessel. Understanding of this area is limited because we currently lack the tools and analytical methods to characterize it. We have previously shown that directional anisotropy of drug delivery can be detected using Directional Fourier Spatial Frequency (DFSF) Analysis. Here we extend this approach to generate flow line maps of nanoparticle transport in TIF relative to tumor ultrastructure, and show that features of tumor spatial heterogeneity can be identified that are directly related to local flow isometries. The identification of these regions of limited flow may be used as a metric for determining response to therapy, or for the optimization of adjuvant therapies such as radiation pre-treatment, or enzymatic degradation.

Investigation of priorities in water quality management based on correlations and variations.

PubMed

Boyacıoğlu, Hülya; Gündogdu, Vildan; Boyacıoğlu, Hayal

2013-04-15

The development of water quality assessment strategies investigating spatial and temporal changes caused by natural and anthropogenic phenomena is an important tool in management practices. This paper used cluster analysis, water quality index method, sensitivity analysis and canonical correlation analysis to investigate priorities in pollution control activities. Data sets representing 22 surface water quality parameters were subject to analysis. Results revealed that organic pollution was serious threat for overall water quality in the region. Besides, oil and grease, lead and mercury were the critical variables violating the standard. In contrast to inorganic variables, organic and physical-inorganic chemical parameters were influenced by variations in physical conditions (discharge, temperature). This study showed that information produced based on the variations and correlations in water quality data sets can be helpful to investigate priorities in water management activities. Moreover statistical techniques and index methods are useful tools in data - information transformation process. Copyright © 2013 Elsevier Ltd. All rights reserved.

Development of an expert analysis tool based on an interactive subsidence hazard map for urban land use in the city of Celaya, Mexico

NASA Astrophysics Data System (ADS)

Alloy, A.; Gonzalez Dominguez, F.; Nila Fonseca, A. L.; Ruangsirikulchai, A.; Gentle, J. N., Jr.; Cabral, E.; Pierce, S. A.

2016-12-01

Land Subsidence as a result of groundwater extraction in central Mexico's larger urban centers initiated in the 80's as a result of population and economic growth. The city of Celaya has undergone subsidence for a few decades and a consequence is the development of an active normal fault system that affects its urban infrastructure and residential areas. To facilitate its analysis and a land use decision-making process we created an online interactive map enabling users to easily obtain information associated with land subsidence. Geological and socioeconomic data of the city was collected, including fault location, population data, and other important infrastructure and structural data has been obtained from fieldwork as part of a study abroad interchange undergraduate course. The subsidence and associated faulting hazard map was created using an InSAR derived subsidence velocity map and population data from INEGI to identify hazard zones using a subsidence gradient spatial analysis approach based on a subsidence gradient and population risk matrix. This interactive map provides a simple perspective of different vulnerable urban elements. As an accessible visualization tool, it will enhance communication between scientific and socio-economic disciplines. Our project also lays the groundwork for a future expert analysis system with an open source and easily accessible Python coded, SQLite database driven website which archives fault and subsidence data along with visual damage documentation to civil structures. This database takes field notes and provides an entry form for uniform datasets, which are used to generate a JSON. Such a database is useful because it allows geoscientists to have a centralized repository and access to their observations over time. Because of the widespread presence of the subsidence phenomena throughout cities in central Mexico, the spatial analysis has been automated using the open source software R. Raster, rgeos, shapefiles, and rgdal libraries have been used to develop the script which permits to obtain the raster maps of horizontal gradient and population density. An advantage is that this analysis can be automated for periodic updates or repurposed for similar analysis in other cities, providing an easily accessible tool for land subsidence hazard assessments.

Programming an Artificial Neural Network Tool for Spatial Interpolation in GIS - A Case Study for Indoor Radio Wave Propagation of WLAN.

PubMed

Sen, Alper; Gümüsay, M Umit; Kavas, Aktül; Bulucu, Umut

2008-09-25

Wireless communication networks offer subscribers the possibilities of free mobility and access to information anywhere at any time. Therefore, electromagnetic coverage calculations are important for wireless mobile communication systems, especially in Wireless Local Area Networks (WLANs). Before any propagation computation is performed, modeling of indoor radio wave propagation needs accurate geographical information in order to avoid the interruption of data transmissions. Geographic Information Systems (GIS) and spatial interpolation techniques are very efficient for performing indoor radio wave propagation modeling. This paper describes the spatial interpolation of electromagnetic field measurements using a feed-forward back-propagation neural network programmed as a tool in GIS. The accuracy of Artificial Neural Networks (ANN) and geostatistical Kriging were compared by adjusting procedures. The feedforward back-propagation ANN provides adequate accuracy for spatial interpolation, but the predictions of Kriging interpolation are more accurate than the selected ANN. The proposed GIS ensures indoor radio wave propagation model and electromagnetic coverage, the number, position and transmitter power of access points and electromagnetic radiation level. Pollution analysis in a given propagation environment was done and it was demonstrated that WLAN (2.4 GHz) electromagnetic coverage does not lead to any electromagnetic pollution due to the low power levels used. Example interpolated electromagnetic field values for WLAN system in a building of Yildiz Technical University, Turkey, were generated using the selected network architectures to illustrate the results with an ANN.

Programming an Artificial Neural Network Tool for Spatial Interpolation in GIS - A Case Study for Indoor Radio Wave Propagation of WLAN

PubMed Central

Şen, Alper; Gümüşay, M. Ümit; Kavas, Aktül; Bulucu, Umut

2008-01-01

Wireless communication networks offer subscribers the possibilities of free mobility and access to information anywhere at any time. Therefore, electromagnetic coverage calculations are important for wireless mobile communication systems, especially in Wireless Local Area Networks (WLANs). Before any propagation computation is performed, modeling of indoor radio wave propagation needs accurate geographical information in order to avoid the interruption of data transmissions. Geographic Information Systems (GIS) and spatial interpolation techniques are very efficient for performing indoor radio wave propagation modeling. This paper describes the spatial interpolation of electromagnetic field measurements using a feed-forward back-propagation neural network programmed as a tool in GIS. The accuracy of Artificial Neural Networks (ANN) and geostatistical Kriging were compared by adjusting procedures. The feedforward back-propagation ANN provides adequate accuracy for spatial interpolation, but the predictions of Kriging interpolation are more accurate than the selected ANN. The proposed GIS ensures indoor radio wave propagation model and electromagnetic coverage, the number, position and transmitter power of access points and electromagnetic radiation level. Pollution analysis in a given propagation environment was done and it was demonstrated that WLAN (2.4 GHz) electromagnetic coverage does not lead to any electromagnetic pollution due to the low power levels used. Example interpolated electromagnetic field values for WLAN system in a building of Yildiz Technical University, Turkey, were generated using the selected network architectures to illustrate the results with an ANN. PMID:27873854

A multi-scale approach of fluvial biogeomorphic dynamics using photogrammetry.

PubMed

Hortobágyi, Borbála; Corenblit, Dov; Vautier, Franck; Steiger, Johannes; Roussel, Erwan; Burkart, Andreas; Peiry, Jean-Luc

2017-11-01

Over the last twenty years, significant technical advances turned photogrammetry into a relevant tool for the integrated analysis of biogeomorphic cross-scale interactions within vegetated fluvial corridors, which will largely contribute to the development and improvement of self-sustainable river restoration efforts. Here, we propose a cost-effective, easily reproducible approach based on stereophotogrammetry and Structure from Motion (SfM) technique to study feedbacks between fluvial geomorphology and riparian vegetation at different nested spatiotemporal scales. We combined different photogrammetric methods and thus were able to investigate biogeomorphic feedbacks at all three spatial scales (i.e., corridor, alluvial bar and micro-site) and at three different temporal scales, i.e., present, recent past and long term evolution on a diversified riparian landscape mosaic. We evaluate the performance and the limits of photogrammetric methods by targeting a set of fundamental parameters necessary to study biogeomorphic feedbacks at each of the three nested spatial scales and, when possible, propose appropriate solutions. The RMSE varies between 0.01 and 2 m depending on spatial scale and photogrammetric methods. Despite some remaining difficulties to properly apply them with current technologies under all circumstances in fluvial biogeomorphic studies, e.g. the detection of vegetation density or landform topography under a dense vegetation canopy, we suggest that photogrammetry is a promising instrument for the quantification of biogeomorphic feedbacks at nested spatial scales within river systems and for developing appropriate river management tools and strategies. Copyright © 2016 Elsevier Ltd. All rights reserved.

Analyzing Human-Landscape Interactions: Tools That Integrate

NASA Astrophysics Data System (ADS)

Zvoleff, Alex; An, Li

2014-01-01

Humans have transformed much of Earth's land surface, giving rise to loss of biodiversity, climate change, and a host of other environmental issues that are affecting human and biophysical systems in unexpected ways. To confront these problems, environmental managers must consider human and landscape systems in integrated ways. This means making use of data obtained from a broad range of methods (e.g., sensors, surveys), while taking into account new findings from the social and biophysical science literatures. New integrative methods (including data fusion, simulation modeling, and participatory approaches) have emerged in recent years to address these challenges, and to allow analysts to provide information that links qualitative and quantitative elements for policymakers. This paper brings attention to these emergent tools while providing an overview of the tools currently in use for analysis of human-landscape interactions. Analysts are now faced with a staggering array of approaches in the human-landscape literature—in an attempt to bring increased clarity to the field, we identify the relative strengths of each tool, and provide guidance to analysts on the areas to which each tool is best applied. We discuss four broad categories of tools: statistical methods (including survival analysis, multi-level modeling, and Bayesian approaches), GIS and spatial analysis methods, simulation approaches (including cellular automata, agent-based modeling, and participatory modeling), and mixed-method techniques (such as alternative futures modeling and integrated assessment). For each tool, we offer an example from the literature of its application in human-landscape research. Among these tools, participatory approaches are gaining prominence for analysts to make the broadest possible array of information available to researchers, environmental managers, and policymakers. Further development of new approaches of data fusion and integration across sites or disciplines pose an important challenge for future work in integrating human and landscape components.

Analysis of multi-mode to single-mode conversion at 635 nm and 1550 nm

NASA Astrophysics Data System (ADS)

Zamora, Vanessa; Bogatzki, Angelina; Arndt-Staufenbiel, Norbert; Hofmann, Jens; Schröder, Henning

2016-03-01

We propose two low-cost and robust optical fiber systems based on the photonic lantern (PL) technology for operating at 635 nm and 1550 nm. The PL is an emerging technology that couples light from a multi-mode (MM) fiber to several single-mode (SM) fibers via a low-loss adiabatic transition. This bundle of SM fibers is observed as a MM fiber system whose spatial modes are the degenerate supermodes of the bundle. The adiabatic transition allows that those supermodes evolve into the modes of the MM fiber. Simulations of the MM fiber end structure and its taper transition have been performed via functional mode solver tools in order to understand the modal evolution in PLs. The modelled design consists of 7 SM fibers inserted into a low-index capillary. The material and geometry of the PLs are chosen such that the supermodes match to the spatial modes of the desired step-index MM fiber in a moderate loss transmission. The dispersion of materials is also considered. These parameters are studied in two PL systems in order to reach a spectral transmission from 450 nm to 1600 nm. Additionally, an analysis of the geometry and losses due to the mismatching of modes is presented. PLs are typically used in the fields of astrophotonics and space photonics. Recently, they are demonstrated as mode converters in telecommunications, especially focusing on spatial division multiplexing. In this study, we show the use of PLs as a promising interconnecting tool for the development of miniaturized spectrometers operating in a broad wavelength range.

Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool

ERIC Educational Resources Information Center

Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román

2014-01-01

This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…

Translating statistical species-habitat models to interactive decision support tools

USGS Publications Warehouse

Wszola, Lyndsie S.; Simonsen, Victoria L.; Stuber, Erica F.; Gillespie, Caitlyn R.; Messinger, Lindsey N.; Decker, Karie L.; Lusk, Jeffrey J.; Jorgensen, Christopher F.; Bishop, Andrew A.; Fontaine, Joseph J.

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

Translating statistical species-habitat models to interactive decision support tools.

PubMed

Wszola, Lyndsie S; Simonsen, Victoria L; Stuber, Erica F; Gillespie, Caitlyn R; Messinger, Lindsey N; Decker, Karie L; Lusk, Jeffrey J; Jorgensen, Christopher F; Bishop, Andrew A; Fontaine, Joseph J

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences.

Translating statistical species-habitat models to interactive decision support tools

PubMed Central

Simonsen, Victoria L.; Stuber, Erica F.; Gillespie, Caitlyn R.; Messinger, Lindsey N.; Decker, Karie L.; Lusk, Jeffrey J.; Jorgensen, Christopher F.; Bishop, Andrew A.; Fontaine, Joseph J.

2017-01-01

Understanding species-habitat relationships is vital to successful conservation, but the tools used to communicate species-habitat relationships are often poorly suited to the information needs of conservation practitioners. Here we present a novel method for translating a statistical species-habitat model, a regression analysis relating ring-necked pheasant abundance to landcover, into an interactive online tool. The Pheasant Habitat Simulator combines the analytical power of the R programming environment with the user-friendly Shiny web interface to create an online platform in which wildlife professionals can explore the effects of variation in local landcover on relative pheasant habitat suitability within spatial scales relevant to individual wildlife managers. Our tool allows users to virtually manipulate the landcover composition of a simulated space to explore how changes in landcover may affect pheasant relative habitat suitability, and guides users through the economic tradeoffs of landscape changes. We offer suggestions for development of similar interactive applications and demonstrate their potential as innovative science delivery tools for diverse professional and public audiences. PMID:29236707

Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis

PubMed Central

Lal, Aparna

2016-01-01

Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change. PMID:26848669

Spatial Modelling Tools to Integrate Public Health and Environmental Science, Illustrated with Infectious Cryptosporidiosis.

PubMed

Lal, Aparna

2016-02-02

Contemporary spatial modelling tools can help examine how environmental exposures such as climate and land use together with socio-economic factors sustain infectious disease transmission in humans. Spatial methods can account for interactions across global and local scales, geographic clustering and continuity of the exposure surface, key characteristics of many environmental influences. Using cryptosporidiosis as an example, this review illustrates how, in resource rich settings, spatial tools have been used to inform targeted intervention strategies and forecast future disease risk with scenarios of environmental change. When used in conjunction with molecular studies, they have helped determine location-specific infection sources and environmental transmission pathways. There is considerable scope for such methods to be used to identify data/infrastructure gaps and establish a baseline of disease burden in resource-limited settings. Spatial methods can help integrate public health and environmental science by identifying the linkages between the physical and socio-economic environment and health outcomes. Understanding the environmental and social context for disease spread is important for assessing the public health implications of projected environmental change.

Coloc-stats: a unified web interface to perform colocalization analysis of genomic features.

PubMed

Simovski, Boris; Kanduri, Chakravarthi; Gundersen, Sveinung; Titov, Dmytro; Domanska, Diana; Bock, Christoph; Bossini-Castillo, Lara; Chikina, Maria; Favorov, Alexander; Layer, Ryan M; Mironov, Andrey A; Quinlan, Aaron R; Sheffield, Nathan C; Trynka, Gosia; Sandve, Geir K

2018-06-05

Functional genomics assays produce sets of genomic regions as one of their main outputs. To biologically interpret such region-sets, researchers often use colocalization analysis, where the statistical significance of colocalization (overlap, spatial proximity) between two or more region-sets is tested. Existing colocalization analysis tools vary in the statistical methodology and analysis approaches, thus potentially providing different conclusions for the same research question. As the findings of colocalization analysis are often the basis for follow-up experiments, it is helpful to use several tools in parallel and to compare the results. We developed the Coloc-stats web service to facilitate such analyses. Coloc-stats provides a unified interface to perform colocalization analysis across various analytical methods and method-specific options (e.g. colocalization measures, resolution, null models). Coloc-stats helps the user to find a method that supports their experimental requirements and allows for a straightforward comparison across methods. Coloc-stats is implemented as a web server with a graphical user interface that assists users with configuring their colocalization analyses. Coloc-stats is freely available at https://hyperbrowser.uio.no/coloc-stats/.

Teaching Spatial Thinking in Undergraduate Geology Courses Using Tools and Strategies from Cognitive Science Research

NASA Astrophysics Data System (ADS)

Ormand, C. J.; Shipley, T. F.; Dutrow, B. L.; Goodwin, L. B.; Hickson, T. A.; Tikoff, B.; Atit, K.; Gagnier, K. M.; Resnick, I.

2015-12-01

Spatial visualization is an essential skill in the STEM disciplines, including the geological sciences. Undergraduate students, including geoscience majors in upper-level courses, bring a wide range of spatial skill levels to the classroom. Students with weak spatial skills may struggle to understand fundamental concepts and to solve geological problems with a spatial component. However, spatial thinking skills are malleable. Using strategies that have emerged from cognitive science research, we developed a set of curricular materials that improve undergraduate geology majors' abilities to reason about 3D concepts and to solve spatially complex geological problems. Cognitive science research on spatial thinking demonstrates that predictive sketching, making visual comparisons, gesturing, and the use of analogy can be used to develop students' spatial thinking skills. We conducted a three-year study of the efficacy of these strategies in strengthening the spatial skills of students in core geology courses at three universities. Our methodology is a quasi-experimental quantitative design, utilizing pre- and post-tests of spatial thinking skills, assessments of spatial problem-solving skills, and a control group comprised of students not exposed to our new curricular materials. Students taught using the new curricular materials show improvement in spatial thinking skills. Further analysis of our data, to be completed prior to AGU, will answer additional questions about the relationship between spatial skills and academic performance, spatial skills and gender, spatial skills and confidence, and the impact of our curricular materials on students who are struggling academically. Teaching spatial thinking in the context of discipline-based exercises has the potential to transform undergraduate education in the geological sciences by removing one significant barrier to success.

Seeing shapes in seemingly random spatial patterns: Fractal analysis of Rorschach inkblots

PubMed Central

Taylor, R. P.; Martin, T. P.; Montgomery, R. D.; Smith, J. H.; Micolich, A. P.; Boydston, C.; Scannell, B. C.; Fairbanks, M. S.; Spehar, B.

2017-01-01

Rorschach inkblots have had a striking impact on the worlds of art and science because of the remarkable variety of associations with recognizable and namable objects they induce. Originally adopted as a projective psychological tool to probe mental health, psychologists and artists have more recently interpreted the variety of induced images simply as a signature of the observers’ creativity. Here we analyze the relationship between the spatial scaling parameters of the inkblot patterns and the number of induced associations, and suggest that the perceived images are induced by the fractal characteristics of the blot edges. We discuss how this relationship explains the frequent observation of images in natural scenery. PMID:28196082

Wavelet packets for multi- and hyper-spectral imagery

NASA Astrophysics Data System (ADS)

Benedetto, J. J.; Czaja, W.; Ehler, M.; Flake, C.; Hirn, M.

2010-01-01

State of the art dimension reduction and classification schemes in multi- and hyper-spectral imaging rely primarily on the information contained in the spectral component. To better capture the joint spatial and spectral data distribution we combine the Wavelet Packet Transform with the linear dimension reduction method of Principal Component Analysis. Each spectral band is decomposed by means of the Wavelet Packet Transform and we consider a joint entropy across all the spectral bands as a tool to exploit the spatial information. Dimension reduction is then applied to the Wavelet Packets coefficients. We present examples of this technique for hyper-spectral satellite imaging. We also investigate the role of various shrinkage techniques to model non-linearity in our approach.

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

PubMed

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

2010-05-01

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

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

PubMed Central

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

2010-01-01

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

Principal component and spatial correlation analysis of spectroscopic-imaging data in scanning probe microscopy.

PubMed

Jesse, Stephen; Kalinin, Sergei V

2009-02-25

An approach for the analysis of multi-dimensional, spectroscopic-imaging data based on principal component analysis (PCA) is explored. PCA selects and ranks relevant response components based on variance within the data. It is shown that for examples with small relative variations between spectra, the first few PCA components closely coincide with results obtained using model fitting, and this is achieved at rates approximately four orders of magnitude faster. For cases with strong response variations, PCA allows an effective approach to rapidly process, de-noise, and compress data. The prospects for PCA combined with correlation function analysis of component maps as a universal tool for data analysis and representation in microscopy are discussed.

An explorative chemometric approach applied to hyperspectral images for the study of illuminated manuscripts

NASA Astrophysics Data System (ADS)

Catelli, Emilio; Randeberg, Lise Lyngsnes; Alsberg, Bjørn Kåre; Gebremariam, Kidane Fanta; Bracci, Silvano

2017-04-01

Hyperspectral imaging (HSI) is a fast non-invasive imaging technology recently applied in the field of art conservation. With the help of chemometrics, important information about the spectral properties and spatial distribution of pigments can be extracted from HSI data. With the intent of expanding the applications of chemometrics to the interpretation of hyperspectral images of historical documents, and, at the same time, to study the colorants and their spatial distribution on ancient illuminated manuscripts, an explorative chemometric approach is here presented. The method makes use of chemometric tools for spectral de-noising (minimum noise fraction (MNF)) and image analysis (multivariate image analysis (MIA) and iterative key set factor analysis (IKSFA)/spectral angle mapper (SAM)) which have given an efficient separation, classification and mapping of colorants from visible-near-infrared (VNIR) hyperspectral images of an ancient illuminated fragment. The identification of colorants was achieved by extracting and interpreting the VNIR spectra as well as by using a portable X-ray fluorescence (XRF) spectrometer.

Seismic slope-performance analysis: from hazard map to decision support system

USGS Publications Warehouse

Miles, Scott B.; Keefer, David K.; Ho, Carlton L.

1999-01-01

In response to the growing recognition of engineers and decision-makers of the regional effects of earthquake-induced landslides, this paper presents a general approach to conducting seismic landslide zonation, based on the popular Newmark's sliding block analogy for modeling coherent landslides. Four existing models based on the sliding block analogy are compared. The comparison shows that the models forecast notably different levels of slope performance. Considering this discrepancy along with the limitations of static maps as a decision tool, a spatial decision support system (SDSS) for seismic landslide analysis is proposed, which will support investigations over multiple scales for any number of earthquake scenarios and input conditions. Most importantly, the SDSS will allow use of any seismic landslide analysis model and zonation approach. Developments associated with the SDSS will produce an object-oriented model for encapsulating spatial data, an object-oriented specification to allow construction of models using modular objects, and a direct-manipulation, dynamic user-interface that adapts to the particular seismic landslide model configuration.

Exploring spatial patterns of farmland transactions and farmland use changes.

PubMed

Chang, Hsueh-Sheng; Chen, Tzu-Ling

2015-09-01

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

Controls on drainage divide migration in the northern Sierras Pampeanas assessed through morphometric indicators

NASA Astrophysics Data System (ADS)

Seagren, E. G.; Schoenbohm, L. M.

2017-12-01

Drainage reorganization, primarily through progressive divide migration leading to discrete stream captures, is increasingly recognized as a common phenomenon during mountain-building events. This drainage rearrangement reflects complex interactions between tectonics, climate, and lithology, and can fundamentally change erosion and sedimentation patterns; therefore, determining the spatial extent and potential controls of divide migration is vital to understanding the topographic evolution of orogenic landscapes. Both geomorphic and morphometric evidence can be used to identify such drainage reorganization. The northern Sierras Pampeanas is an ideal location in which to study divide migration as limited glaciation and low out-of-channel erosion rates preserve evidence of reorganization. Additionally, several ranges in the region, such as Sierra de las Planchadas, exhibit geomorphic evidence of drainage rearrangement, including wind gaps and hairpin turns. Using ArcGIS, LSDTopoTools, and TopoToolbox, we conducted a systematic analysis of the spatial distribution of three morphometric indicators of divide migration: χ, Mx, and local headwater relief. Local `hotspots' undergoing drainage divide migration were identified using spatial autocorrelation and clustering methods - Gi* and Moran's I. Using spatial regression analysis, we assessed the potential controls of lithology, modern TRMM precipitation rates, and tectonics over divide migration. Preliminary results suggest broad westward migration of main drainage divides, following both the orographic precipitation gradient and regional slope.

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

PubMed

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

2007-01-01

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

Integrating landscape analysis and planning: a multi-scale approach for oriented management of tourist recreation.

PubMed

de Aranzabal, Itziar; Schmitz, María F; Pineda, Francisco D

2009-11-01

Tourism and landscape are interdependent concepts. Nature- and culture-based tourism are now quite well developed activities and can constitute an excellent way of exploiting the natural resources of certain areas, and should therefore be considered as key objectives in landscape planning and management in a growing number of countries. All of this calls for careful evaluation of the effects of tourism on the territory. This article focuses on an integrated spatial method for landscape analysis aimed at quantifying the relationship between preferences of visitors and landscape features. The spatial expression of the model relating types of leisure and recreational preferences to the potential capacity of the landscape to meet them involves a set of maps showing degrees of potential visitor satisfaction. The method constitutes a useful tool for the design of tourism planning and management strategies, with landscape conservation as a reference.

Hyperspectral imaging for non-contact analysis of forensic traces.

PubMed

Edelman, G J; Gaston, E; van Leeuwen, T G; Cullen, P J; Aalders, M C G

2012-11-30

Hyperspectral imaging (HSI) integrates conventional imaging and spectroscopy, to obtain both spatial and spectral information from a specimen. This technique enables investigators to analyze the chemical composition of traces and simultaneously visualize their spatial distribution. HSI offers significant potential for the detection, visualization, identification and age estimation of forensic traces. The rapid, non-destructive and non-contact features of HSI mark its suitability as an analytical tool for forensic science. This paper provides an overview of the principles, instrumentation and analytical techniques involved in hyperspectral imaging. We describe recent advances in HSI technology motivating forensic science applications, e.g. the development of portable and fast image acquisition systems. Reported forensic science applications are reviewed. Challenges are addressed, such as the analysis of traces on backgrounds encountered in casework, concluded by a summary of possible future applications. Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.

Self-organizing maps: a versatile tool for the automatic analysis of untargeted imaging datasets.

PubMed

Franceschi, Pietro; Wehrens, Ron

2014-04-01

MS-based imaging approaches allow for location-specific identification of chemical components in biological samples, opening up possibilities of much more detailed understanding of biological processes and mechanisms. Data analysis, however, is challenging, mainly because of the sheer size of such datasets. This article presents a novel approach based on self-organizing maps, extending previous work in order to be able to handle the large number of variables present in high-resolution mass spectra. The key idea is to generate prototype images, representing spatial distributions of ions, rather than prototypical mass spectra. This allows for a two-stage approach, first generating typical spatial distributions and associated m/z bins, and later analyzing the interesting bins in more detail using accurate masses. The possibilities and advantages of the new approach are illustrated on an in-house dataset of apple slices. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

The design of instructional tools affects secondary school students' learning of cardiopulmonary resuscitation (CPR) in reciprocal peer learning: a randomized controlled trial.

PubMed

Iserbyt, Peter; Byra, Mark

2013-11-01

Research investigating design effects of instructional tools for learning Basic Life Support (BLS) is almost non-existent. To demonstrate the design of instructional tools matter. The effect of spatial contiguity, a design principle stating that people learn more deeply when words and corresponding pictures are placed close (i.e., integrated) rather than far from each other on a page was investigated on task cards for learning Cardiopulmonary Resuscitation (CPR) during reciprocal peer learning. A randomized controlled trial. A total of 111 students (mean age: 13 years) constituting six intact classes learned BLS through reciprocal learning with task cards. Task cards combine a picture of the skill with written instructions about how to perform it. In each class, students were randomly assigned to the experimental group or the control. In the control, written instructions were placed under the picture on the task cards. In the experimental group, written instructions were placed close to the corresponding part of the picture on the task cards reflecting application of the spatial contiguity principle. One-way analysis of variance found significantly better performances in the experimental group for ventilation volumes (P=.03, ηp2=.10) and flow rates (P=.02, ηp2=.10). For chest compression depth, compression frequency, compressions with correct hand placement, and duty cycles no significant differences were found. This study shows that the design of instructional tools (i.e., task cards) affects student learning. Research-based design of learning tools can enhance BLS and CPR education. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

[Ecological risk assessment of land use based on exploratory spatial data analysis (ESDA): a case study of Haitan Island, Fujian Province].

PubMed

Wu, Jian; Chen, Peng; Wen, Chao-Xiang; Fu, Shi-Feng; Chen, Qing-Hui

2014-07-01

As a novel environment management tool, ecological risk assessment has provided a new perspective for the quantitative evaluation of ecological effects of land-use change. In this study, Haitan Island in Fujian Province was taken as a case. Based on the Landsat TM obtained in 1990, SPOT5 RS images obtained in 2010, general layout planning map of Pingtan Comprehensive Experimental Zone in 2030, as well as the field investigation data, we established an ecological risk index to measure ecological endpoints. By using spatial autocorrelation and semivariance analysis of Exploratory Spatial Data Analysis (ESDA), the ecological risk of Haitan Island under different land-use situations was assessed, including the past (1990), present (2010) and future (2030), and the potential risk and its changing trend were analyzed. The results revealed that the ecological risk index showed obvious scale effect, with strong positive correlation within 3000 meters. High-high (HH) and low-low (LL) aggregations were predominant types in spatial distribution of ecological risk index. The ecological risk index showed significant isotropic characteristics, and its spatial distribution was consistent with Anselin Local Moran I (LISA) distribution during the same period. Dramatic spatial distribution change of each ecological risk area was found among 1990, 2010 and 2030, and the fluctuation trend and amplitude of different ecological risk areas were diverse. The low ecological risk area showed a rise-to-fall trend while the medium and high ecological risk areas showed a fall-to-rise trend. In the planning period, due to intensive anthropogenic disturbance, the high ecological risk area spread throughout the whole region. To reduce the ecological risk in land-use and maintain the regional ecological security, the following ecological risk control strategies could be adopted, i.e., optimizing the spatial pattern of land resources, protecting the key ecoregions and controlling the scale of construction land use.

Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs.

PubMed

Teshager, Awoke Dagnew; Gassman, Philip W; Secchi, Silvia; Schoof, Justin T; Misgna, Girmaye

2016-04-01

Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

Modeling Agricultural Watersheds with the Soil and Water Assessment Tool (SWAT): Calibration and Validation with a Novel Procedure for Spatially Explicit HRUs

NASA Astrophysics Data System (ADS)

Teshager, Awoke Dagnew; Gassman, Philip W.; Secchi, Silvia; Schoof, Justin T.; Misgna, Girmaye

2016-04-01

Applications of the Soil and Water Assessment Tool (SWAT) model typically involve delineation of a watershed into subwatersheds/subbasins that are then further subdivided into hydrologic response units (HRUs) which are homogeneous areas of aggregated soil, landuse, and slope and are the smallest modeling units used within the model. In a given standard SWAT application, multiple potential HRUs (farm fields) in a subbasin are usually aggregated into a single HRU feature. In other words, the standard version of the model combines multiple potential HRUs (farm fields) with the same landuse/landcover, soil, and slope, but located at different places of a subbasin (spatially non-unique), and considers them as one HRU. In this study, ArcGIS pre-processing procedures were developed to spatially define a one-to-one match between farm fields and HRUs (spatially unique HRUs) within a subbasin prior to SWAT simulations to facilitate input processing, input/output mapping, and further analysis at the individual farm field level. Model input data such as landuse/landcover (LULC), soil, crop rotation, and other management data were processed through these HRUs. The SWAT model was then calibrated/validated for Raccoon River watershed in Iowa for 2002-2010 and Big Creek River watershed in Illinois for 2000-2003. SWAT was able to replicate annual, monthly, and daily streamflow, as well as sediment, nitrate and mineral phosphorous within recommended accuracy in most cases. The one-to-one match between farm fields and HRUs created and used in this study is a first step in performing LULC change, climate change impact, and other analyses in a more spatially explicit manner.

Factors affecting private forest landowner interest in ecosystem management: linking spatial and survey data.

PubMed

Jacobson, Michael G

2002-10-01

Many factors influence forest landowner management decisions. This study examines landowner decisions regarding participation in ecosystem management activities, such as a landscape corridor cutting across their private lands. Landscape corridors are recognized worldwide as an important tool in biodiversity conservation. For ecosystem management activities to occur in areas dominated by a multitude of small private forest landholdings, landowner participation and cooperation is necessary. Data from a survey of landowners combined with an analysis of their land's spatial attributes is used to assess their interest in ecosystem management. Results suggest that spatial attributes are not good predictors of an owner's interest in ecosystem management. Other factors such as attitudes and opinions about the environment are more effective in explaining landowner interest. The results have implications for any land manager using GIS data and implementing ecosystem management activities on private forestland.

Estimating Prediction Uncertainty from Geographical Information System Raster Processing: A User's Manual for the Raster Error Propagation Tool (REPTool)

USGS Publications Warehouse

Gurdak, Jason J.; Qi, Sharon L.; Geisler, Michael L.

2009-01-01

The U.S. Geological Survey Raster Error Propagation Tool (REPTool) is a custom tool for use with the Environmental System Research Institute (ESRI) ArcGIS Desktop application to estimate error propagation and prediction uncertainty in raster processing operations and geospatial modeling. REPTool is designed to introduce concepts of error and uncertainty in geospatial data and modeling and provide users of ArcGIS Desktop a geoprocessing tool and methodology to consider how error affects geospatial model output. Similar to other geoprocessing tools available in ArcGIS Desktop, REPTool can be run from a dialog window, from the ArcMap command line, or from a Python script. REPTool consists of public-domain, Python-based packages that implement Latin Hypercube Sampling within a probabilistic framework to track error propagation in geospatial models and quantitatively estimate the uncertainty of the model output. Users may specify error for each input raster or model coefficient represented in the geospatial model. The error for the input rasters may be specified as either spatially invariant or spatially variable across the spatial domain. Users may specify model output as a distribution of uncertainty for each raster cell. REPTool uses the Relative Variance Contribution method to quantify the relative error contribution from the two primary components in the geospatial model - errors in the model input data and coefficients of the model variables. REPTool is appropriate for many types of geospatial processing operations, modeling applications, and related research questions, including applications that consider spatially invariant or spatially variable error in geospatial data.

Quantifying the Temporal Inequality of Nutrient Loads with a Novel Metric

NASA Astrophysics Data System (ADS)

Gall, H. E.; Schultz, D.; Rao, P. S.; Jawitz, J. W.; Royer, M.

2015-12-01

Inequality is an emergent property of many complex systems. For a given series of stochastic events, some events generate a disproportionately large contribution to system responses compared to other events. In catchments, such responses cause streamflow and solute loads to exhibit strong temporal inequality, with the vast majority of discharge and solute loads exported during short periods of time during which high-flow events occur. These periods of time are commonly referred to as "hot moments". Although this temporal inequality is widely recognized, there is currently no uniform metric for assessing it. We used a novel application of Lorenz Inequality, a method commonly used in economics to quantify income inequality, to quantify the spatial and temporal inequality of streamflow and nutrient (nitrogen and phosphorus) loads exported to the Chesapeake Bay. Lorenz Inequality and the corresponding Gini Coefficient provide an analytical tool for quantifying inequality that can be applied at any temporal or spatial scale. The Gini coefficient (G) is a formal measure of inequality that varies from 0 to 1, with a value of 0 indicating perfect equality (i.e., fluxes and loads are constant in time) and 1 indicating perfect inequality (i.e., all of the discharge and solute loads are exported during one instant in time). Therefore, G is a simple yet powerful tool for providing insight into the temporal inequality of nutrient transport. We will present the results of our detailed analysis of streamflow and nutrient time series data collected since the early 1980's at 30 USGS gauging stations in the Chesapeake Bay watershed. The analysis is conducted at an annual time scale, enabling trends and patterns to be assessed both temporally (over time at each station) and spatially (for the same period of time across stations). The results of this analysis have the potential to create a transformative new framework for identifying "hot moments", improving our ability to temporally and spatially target implementation of best management practices to ultimately improve water quality in the Chesapeake Bay. This method also provides insight into the temporal scales at which hydrologic and biogeochemical variability dominate nutrient export dynamics.

Modeling languages for biochemical network simulation: reaction vs equation based approaches.

PubMed

Wiechert, Wolfgang; Noack, Stephan; Elsheikh, Atya

2010-01-01

Biochemical network modeling and simulation is an essential task in any systems biology project. The systems biology markup language (SBML) was established as a standardized model exchange language for mechanistic models. A specific strength of SBML is that numerous tools for formulating, processing, simulation and analysis of models are freely available. Interestingly, in the field of multidisciplinary simulation, the problem of model exchange between different simulation tools occurred much earlier. Several general modeling languages like Modelica have been developed in the 1990s. Modelica enables an equation based modular specification of arbitrary hierarchical differential algebraic equation models. Moreover, libraries for special application domains can be rapidly developed. This contribution compares the reaction based approach of SBML with the equation based approach of Modelica and explains the specific strengths of both tools. Several biological examples illustrating essential SBML and Modelica concepts are given. The chosen criteria for tool comparison are flexibility for constraint specification, different modeling flavors, hierarchical, modular and multidisciplinary modeling. Additionally, support for spatially distributed systems, event handling and network analysis features is discussed. As a major result it is shown that the choice of the modeling tool has a strong impact on the expressivity of the specified models but also strongly depends on the requirements of the application context.

GeoProMT: A Collaborative Platform Supporting Natural Hazards Project Management From Assessment to Resilience

NASA Astrophysics Data System (ADS)

Renschler, C.; Sheridan, M. F.; Patra, A. K.

2008-05-01

The impact and consequences of extreme geophysical events (hurricanes, floods, wildfires, volcanic flows, mudflows, etc.) on properties and processes should be continuously assessed by a well-coordinated interdisciplinary research and outreach approach addressing risk assessment and resilience. Communication between various involved disciplines and stakeholders is the key to a successful implementation of an integrated risk management plan. These issues become apparent at the level of decision support tools for extreme events/disaster management in natural and managed environments. The Geospatial Project Management Tool (GeoProMT) is a collaborative platform for research and training to document and communicate the fundamental steps in transforming information for extreme events at various scales for analysis and management. GeoProMT is an internet-based interface for the management of shared geo-spatial and multi-temporal information such as measurements, remotely sensed images, and other GIS data. This tool enhances collaborative research activities and the ability to assimilate data from diverse sources by integrating information management. This facilitates a better understanding of natural processes and enhances the integrated assessment of resilience against both the slow and fast onset of hazard risks. Fundamental to understanding and communicating complex natural processes are: (a) representation of spatiotemporal variability, extremes, and uncertainty of environmental properties and processes in the digital domain, (b) transformation of their spatiotemporal representation across scales (e.g. interpolation, aggregation, disaggregation.) during data processing and modeling in the digital domain, and designing and developing tools for (c) geo-spatial data management, and (d) geo-spatial process modeling and effective implementation, and (e) supporting decision- and policy-making in natural resources and hazard management at various spatial and temporal scales of interest. GeoProMT is useful for researchers, practitioners, and decision-makers, because it provides an integrated environmental system assessment and data management approach that considers the spatial and temporal scales and variability in natural processes. Particularly in the occurrence or onset of extreme events it can utilize the latest data sources that are available at variable scales, combine them with existing information, and update assessment products such as risk and vulnerability assessment maps. Because integrated geo-spatial assessment requires careful consideration of all the steps in utilizing data, modeling and decision-making formats, each step in the sequence must be assessed in terms of how information is being scaled. At the process scale various geophysical models (e.g. TITAN, LAHARZ, or many other examples) are appropriate for incorporation in the tool. Some examples that illustrate our approach include: 1) coastal parishes impacted by Hurricane Rita (Southwestern Louisiana), 2) a watershed affected by extreme rainfall induced debris-flows (Madison County, Virginia; Panabaj, Guatemala; Casita, Nicaragua), and 3) the potential for pyroclastic flows to threaten a city (Tungurahua, Ecuador). This research was supported by the National Science Foundation.

FluoRender: joint freehand segmentation and visualization for many-channel fluorescence data analysis.

PubMed

Wan, Yong; Otsuna, Hideo; Holman, Holly A; Bagley, Brig; Ito, Masayoshi; Lewis, A Kelsey; Colasanto, Mary; Kardon, Gabrielle; Ito, Kei; Hansen, Charles

2017-05-26

Image segmentation and registration techniques have enabled biologists to place large amounts of volume data from fluorescence microscopy, morphed three-dimensionally, onto a common spatial frame. Existing tools built on volume visualization pipelines for single channel or red-green-blue (RGB) channels have become inadequate for the new challenges of fluorescence microscopy. For a three-dimensional atlas of the insect nervous system, hundreds of volume channels are rendered simultaneously, whereas fluorescence intensity values from each channel need to be preserved for versatile adjustment and analysis. Although several existing tools have incorporated support of multichannel data using various strategies, the lack of a flexible design has made true many-channel visualization and analysis unavailable. The most common practice for many-channel volume data presentation is still converting and rendering pseudosurfaces, which are inaccurate for both qualitative and quantitative evaluations. Here, we present an alternative design strategy that accommodates the visualization and analysis of about 100 volume channels, each of which can be interactively adjusted, selected, and segmented using freehand tools. Our multichannel visualization includes a multilevel streaming pipeline plus a triple-buffer compositing technique. Our method also preserves original fluorescence intensity values on graphics hardware, a crucial feature that allows graphics-processing-unit (GPU)-based processing for interactive data analysis, such as freehand segmentation. We have implemented the design strategies as a thorough restructuring of our original tool, FluoRender. The redesign of FluoRender not only maintains the existing multichannel capabilities for a greatly extended number of volume channels, but also enables new analysis functions for many-channel data from emerging biomedical-imaging techniques.

Data Basin: Expanding Access to Conservation Data, Tools, and People

NASA Astrophysics Data System (ADS)

Comendant, T.; Strittholt, J.; Frost, P.; Ward, B. C.; Bachelet, D. M.; Osborne-Gowey, J.

2009-12-01

Mapping and spatial analysis are a fundamental part of problem solving in conservation science, yet spatial data are widely scattered, difficult to locate, and often unavailable. Valuable time and resources are wasted locating and gaining access to important biological, cultural, and economic datasets, scientific analysis, and experts. As conservation problems become more serious and the demand to solve them grows more urgent, a new way to connect science and practice is needed. To meet this need, an open-access, web tool called Data Basin (www.databasin.org) has been created by the Conservation Biology Institute in partnership with ESRI and the Wilburforce Foundation. Users of Data Basin can gain quick access to datasets, experts, groups, and tools to help solve real-world problems. Individuals and organizations can perform essential tasks such as exploring and downloading from a vast library of conservation datasets, uploading existing datasets, connecting to other external data sources, create groups, and produce customized maps that can be easily shared. Data Basin encourages sharing and publishing, but also provides privacy and security for sensitive information when needed. Users can publish projects within Data Basin to tell more complete and rich stories of discovery and solutions. Projects are an ideal way to publish collections of datasets, maps and other information on the internet to reach wider audiences. Data Basin also houses individual centers that provide direct access to data, maps, and experts focused on specific geographic areas or conservation topics. Current centers being developed include the Boreal Information Centre, the Data Basin Climate Center, and proposed Aquatic and Forest Conservation Centers.

GIS Tools to Estimate Average Annual Daily Traffic

DOT National Transportation Integrated Search

2012-06-01

This project presents five tools that were created for a geographical information system to estimate Annual Average Daily : Traffic using linear regression. Three of the tools can be used to prepare spatial data for linear regression. One tool can be...

Prediction of soil stability and erosion in semiarid regions using numerical hydrological model (MCAT) and airborne hyperspectral imagery

NASA Astrophysics Data System (ADS)

Brook, Anna; Wittenberg, Lea

2015-04-01

Long-term environmental monitoring is addressed to identify physical and biological changes and progresses taking place in the ecosystem. This basic action of landscape monitoring is an essential part of the systematic long-term surveillance, aiming to evaluate, assess and predict the spatial change and progresses. Indeed, it provides a context for wide range of diverse studies and research frameworks from regional or global scale. Spatial-temporal trends and changes at various scales (massive to less certain) require establishing consistent baseline data over time. One of the spatial cases of landscape monitoring is dedicated to soil formation and pedological progresses. It is previously acknowledged that changes in soil affect the functionality of the environment, so monitoring changes recently become important cause considerable resources in areas such as environmental management, sustainability services, and protecting the environment healthy. Given the above, it can be concluded that monitoring changes in the base for sustainable development. The hydrological response of bare soils and watersheds in semiarid regions to intense rainfall events is known to be complex due to multiply physical and structural impacts and feedbacks. As a result, the comprehensive evaluations of mathematical models including detailed consideration of uncertainties in the modeling of hydrological and environmental systems are of increasing importance. The presented method incorporates means of remote sensing data, hydrological and climate data and implementing dedicated and integrative Monte Carlo Analysis Toolbox (MCAT) model for semiarid region. Complexity of practical models to represent spatial systems requires an extensive understanding of the spatial phenomena, while providing realistic balance of sensitivity and corresponding uncertainty levels. Nowadays a large number of dedicated mathematical models applied to assess environmental hydrological process. Among the most promising models is the MCAT, which is a MATLAB library of visual and numerical analysis tools for the evaluation of hydrological and environmental models. The model applied in this paper presents an innovative infrastructural system for predicting soil stability and erosion impacts. This integrated model is applicable to mixed areas with spatially varying soil properties, landscape, and land-cover characteristics. Data from a semiarid site in southern Israel was used to evaluate the model and analyze fundamental erosion mechanisms. The findings estimate the sensitivity of the suggested model to the physical parameters and encourage the use of hyperspectral remote sensing imagery (HSI). The proposed model is integrated according to the following stages: 1. The soil texture, aggregation, soil moisture estimated via airborne HSI data, including soil surface clay and calcium carbonate erosions; 2. The mechanical stability of soil assessed via pedo-transfer function corresponding to load dependent changes in soil physical properties due to pre-compression stress (set of equations study shear strength parameters take into account soil texture, aggregation, soil moisture and ecological soil variables); 3. The precipitation-related runoff model program (RMP) satisfactorily reproduces the observed seasonal mean and variation of surface runoff for the current climate simulation; 4. The Monte Carlo Analysis Toolbox (MCAT), a library of visual and numerical analysis tools for the evaluation of hydrological and environmental models, is proposed as a tool for integrate all the approaches to an applicable model. The presented model overcomes the limitations of existing modeling methods by integrating physical data produced via HSI and yet stays generic in terms of space and time independency.

Application of the CO2-PENS risk analysis tool to the Rock Springs Uplift, Wyoming

USGS Publications Warehouse

Stauffer, P.H.; Pawar, R.J.; Surdam, R.C.; Jiao, Z.; Deng, H.; Lettelier, B.C.; Viswanathan, H.S.; Sanzo, D.L.; Keating, G.N.

2011-01-01

We describe preliminary application of the CO2-PENS performance and risk analysis tool to a planned geologic CO2 sequestration demonstration project in the Rock Springs Uplift (RSU), located in south western Wyoming. We use data from the RSU to populate CO2-PENS, an evolving system-level modeling tool developed at Los Alamos National Laboratory. This tool has been designed to generate performance and risk assessment calculations for the geologic sequestration of carbon dioxide. Our approach follows Systems Analysis logic and includes estimates of uncertainty in model parameters and Monte-Carlo simulations that lead to probabilistic results. Probabilistic results provide decision makers with a range in the likelihood of different outcomes. Herein we present results from a newly implemented approach in CO 2-PENS that captures site-specific spatially coherent details such as topography on the reservoir/cap-rock interface, changes in saturation and pressure during injection, and dip on overlying aquifers that may be impacted by leakage upward through wellbores and faults. We present simulations of CO 2 injection under different uncertainty distributions for hypothetical leaking wells and faults. Although results are preliminary and to be used only for demonstration of the approach, future results of the risk analysis will form the basis for a discussion on methods to reduce uncertainty in the risk calculations. Additionally, we present ideas on using the model to help locate monitoring equipment to detect potential leaks. By maintaining site-specific details in the CO2-PENS analysis we provide a tool that allows more logical presentations to stakeholders in the region. ?? 2011 Published by Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

Golay, Jean; Kanevski, Mikhaïl

2013-04-01

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

Valuing investments in sustainable land management using an integrated modelling framework to support a watershed conservation scheme in the Upper Tana River, Kenya

NASA Astrophysics Data System (ADS)

Hunink, Johannes E.; Bryant, Benjamin P.; Vogl, Adrian; Droogers, Peter

2015-04-01

We analyse the multiple impacts of investments in sustainable land use practices on ecosystem services in the Upper Tana basin (Kenya) to support a watershed conservation scheme (a "water fund"). We apply an integrated modelling framework, building on previous field-based and modelling studies in the basin, and link biophysical outputs to economic benefits for the main actors in the basin. The first step in the modelling workflow is the use of a high-resolution spatial prioritization tool (Resource Investment Optimization System -- RIOS) to allocate the type and location of conservation investments in the different subbasins, subject to budget constraints and stakeholder concerns. We then run the Soil and Water Assessment Tool (SWAT) using the RIOS-identified investment scenarios to produce spatially explicit scenarios that simulate changes in water yield and suspended sediment. Finally, in close collaboration with downstream water users (urban water supply and hydropower) we link those biophysical outputs to monetary metrics, including: reduced water treatment costs, increased hydropower production, and crop yield benefits for upstream farmers in the conservation area. We explore how different budgets and different spatial targeting scenarios influence the return of the investments and the effectiveness of the water fund scheme. This study is novel in that it presents an integrated analysis targeting interventions in a decision context that takes into account local environmental and socio-economic conditions, and then relies on detailed, process-based, biophysical models to demonstrate the economic return on those investments. We conclude that the approach allows for an analysis on different spatial and temporal scales, providing conclusive evidence to stakeholders and decision makers on the contribution and benefits of the land-based investments in this basin. This is serving as foundational work to support the implementation of the Upper Tana-Nairobi Water Fund, a public-private partnership to safeguard ecosystem service provision and food security.

Addressing uncertainty in modelling cumulative impacts within maritime spatial planning in the Adriatic and Ionian region.

PubMed

Gissi, Elena; Menegon, Stefano; Sarretta, Alessandro; Appiotti, Federica; Maragno, Denis; Vianello, Andrea; Depellegrin, Daniel; Venier, Chiara; Barbanti, Andrea

2017-01-01

Maritime spatial planning (MSP) is envisaged as a tool to apply an ecosystem-based approach to the marine and coastal realms, aiming at ensuring that the collective pressure of human activities is kept within acceptable limits. Cumulative impacts (CI) assessment can support science-based MSP, in order to understand the existing and potential impacts of human uses on the marine environment. A CI assessment includes several sources of uncertainty that can hinder the correct interpretation of its results if not explicitly incorporated in the decision-making process. This study proposes a three-level methodology to perform a general uncertainty analysis integrated with the CI assessment for MSP, applied to the Adriatic and Ionian Region (AIR). We describe the nature and level of uncertainty with the help of expert judgement and elicitation to include all of the possible sources of uncertainty related to the CI model with assumptions and gaps related to the case-based MSP process in the AIR. Next, we use the results to tailor the global uncertainty analysis to spatially describe the uncertainty distribution and variations of the CI scores dependent on the CI model factors. The results show the variability of the uncertainty in the AIR, with only limited portions robustly identified as the most or the least impacted areas under multiple model factors hypothesis. The results are discussed for the level and type of reliable information and insights they provide to decision-making. The most significant uncertainty factors are identified to facilitate the adaptive MSP process and to establish research priorities to fill knowledge gaps for subsequent planning cycles. The method aims to depict the potential CI effects, as well as the extent and spatial variation of the data and scientific uncertainty; therefore, this method constitutes a suitable tool to inform the potential establishment of the precautionary principle in MSP.

The Spectral Image Processing System (SIPS) - Interactive visualization and analysis of imaging spectrometer data

NASA Technical Reports Server (NTRS)

Kruse, F. A.; Lefkoff, A. B.; Boardman, J. W.; Heidebrecht, K. B.; Shapiro, A. T.; Barloon, P. J.; Goetz, A. F. H.

1993-01-01

The Center for the Study of Earth from Space (CSES) at the University of Colorado, Boulder, has developed a prototype interactive software system called the Spectral Image Processing System (SIPS) using IDL (the Interactive Data Language) on UNIX-based workstations. SIPS is designed to take advantage of the combination of high spectral resolution and spatial data presentation unique to imaging spectrometers. It streamlines analysis of these data by allowing scientists to rapidly interact with entire datasets. SIPS provides visualization tools for rapid exploratory analysis and numerical tools for quantitative modeling. The user interface is X-Windows-based, user friendly, and provides 'point and click' operation. SIPS is being used for multidisciplinary research concentrating on use of physically based analysis methods to enhance scientific results from imaging spectrometer data. The objective of this continuing effort is to develop operational techniques for quantitative analysis of imaging spectrometer data and to make them available to the scientific community prior to the launch of imaging spectrometer satellite systems such as the Earth Observing System (EOS) High Resolution Imaging Spectrometer (HIRIS).

Maritime Spatial Planning supported by systematic site selection: Applying Marxan for offshore wind power in the western Baltic Sea

PubMed Central

Dahl, Karsten; Mohn, Christian

2018-01-01

The development of offshore wind energy and other competing interests in sea space are a major incentive for designating marine and coastal areas for specific human activities. Maritime Spatial Planning (MSP) considers human activities at sea in a more integrated way by analysing and designating spatial and temporal distributions of human activities based on ecological, economic and social targets. However, specific tools supporting spatial decisions at sea incorporating all relevant sectors are rarely adopted. The decision support tool Marxan is traditionally used for systematic selection and designation of nature protection and conservation areas. In this study, Marxan was applied as a support tool to identify suitable sites for offshore wind power in the pilot area Pomeranian Bight / Arkona Basin in the western Baltic Sea. The software was successfully tested and scenarios were developed that support the sites indicated in existing national plans, but also show options for alternative developments of offshore wind power in the Pomeranian Bight / Arkona Basin area. PMID:29543878

Surface Desorption Dielectric-Barrier Discharge Ionization Mass Spectrometry.

PubMed

Zhang, Hong; Jiang, Jie; Li, Na; Li, Ming; Wang, Yingying; He, Jing; You, Hong

2017-07-18

A variant of dielectric-barrier discharge named surface desorption dielectric-barrier discharge ionization (SDDBDI) mass spectrometry was developed for high-efficiency ion transmission and high spatial resolution imaging. In SDDBDI, a tungsten nanotip and the inlet of the mass spectrometer are used as electrodes, and a piece of coverslip is used as a sample plate as well as an insulating dielectric barrier, which simplifies the configuration of instrument and thus the operation. Different from volume dielectric-barrier discharge (VDBD), the microdischarges are generated on the surface at SDDBDI, and therefore the plasma density is extremely high. Analyte ions are guided directly into the MS inlet without any deflection. This configuration significantly improves the ion transmission efficiency and thus the sensitivity. The dependence of sensitivity and spatial resolution of the SDDBDI on the operation parameters were systematically investigated. The application of SDDBDI was successfully demonstrated by analysis of multiple species including amino acids, pharmaceuticals, putative cancer biomarkers, and mixtures of both fatty acids and hormones. Limits of detection (S/N = 3) were determined to be 0.84 and 0.18 pmol, respectively, for the analysis of l-alanine and metronidazole. A spatial resolution of 22 μm was obtained for the analysis of an imprinted cyclophosphamide pattern, and imaging of a "T" character was successfully demonstrated under ambient conditions. These results indicate that SDDBDI has high-efficiency ion transmission, high sensitivity, and high spatial resolution, which render it a potential tool for mass spectrometry imaging.

Geostatistical applications in environmental remediation

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

Stewart, R.N.; Purucker, S.T.; Lyon, B.F.

1995-02-01

Geostatistical analysis refers to a collection of statistical methods for addressing data that vary in space. By incorporating spatial information into the analysis, geostatistics has advantages over traditional statistical analysis for problems with a spatial context. Geostatistics has a history of success in earth science applications, and its popularity is increasing in other areas, including environmental remediation. Due to recent advances in computer technology, geostatistical algorithms can be executed at a speed comparable to many standard statistical software packages. When used responsibly, geostatistics is a systematic and defensible tool can be used in various decision frameworks, such as the Datamore » Quality Objectives (DQO) process. At every point in the site, geostatistics can estimate both the concentration level and the probability or risk of exceeding a given value. Using these probability maps can assist in identifying clean-up zones. Given any decision threshold and an acceptable level of risk, the probability maps identify those areas that are estimated to be above or below the acceptable risk. Those areas that are above the threshold are of the most concern with regard to remediation. In addition to estimating clean-up zones, geostatistics can assist in designing cost-effective secondary sampling schemes. Those areas of the probability map with high levels of estimated uncertainty are areas where more secondary sampling should occur. In addition, geostatistics has the ability to incorporate soft data directly into the analysis. These data include historical records, a highly correlated secondary contaminant, or expert judgment. The role of geostatistics in environmental remediation is a tool that in conjunction with other methods can provide a common forum for building consensus.« less

Evaluating the utility of companion animal tick surveillance practices for monitoring spread and occurrence of human Lyme disease in West Virginia, 2014-2016.

PubMed

Hendricks, Brian; Mark-Carew, Miguella; Conley, Jamison

2017-11-13

Domestic dogs and cats are potentially effective sentinel populations for monitoring occurrence and spread of Lyme disease. Few studies have evaluated the public health utility of sentinel programmes using geo-analytic approaches. Confirmed Lyme disease cases diagnosed by physicians and ticks submitted by veterinarians to the West Virginia State Health Department were obtained for 2014-2016. Ticks were identified to species, and only Ixodes scapularis were incorporated in the analysis. Separate ordinary least squares (OLS) and spatial lag regression models were conducted to estimate the association between average numbers of Ix. scapularis collected on pets and human Lyme disease incidence. Regression residuals were visualised using Local Moran's I as a diagnostic tool to identify spatial dependence. Statistically significant associations were identified between average numbers of Ix. scapularis collected from dogs and human Lyme disease in the OLS (β=20.7, P<0.001) and spatial lag (β=12.0, P=0.002) regression. No significant associations were identified for cats in either regression model. Statistically significant (P≤0.05) spatial dependence was identified in all regression models. Local Moran's I maps produced for spatial lag regression residuals indicated a decrease in model over- and under-estimation, but identified a higher number of statistically significant outliers than OLS regression. Results support previous conclusions that dogs are effective sentinel populations for monitoring risk of human exposure to Lyme disease. Findings reinforce the utility of spatial analysis of surveillance data, and highlight West Virginia's unique position within the eastern United States in regards to Lyme disease occurrence.

Alcohol beverage control, privatization and the geographic distribution of alcohol outlets

PubMed Central

2012-01-01

Background With Pennsylvania currently considering a move away from an Alcohol Beverage Control state to a privatized alcohol distribution system, this study uses a spatial analytical approach to examine potential impacts of privatization on the number and spatial distribution of alcohol outlets in the city of Philadelphia over a long time horizon. Methods A suite of geospatial data were acquired for Philadelphia, including 1,964 alcohol outlet locations, 569,928 land parcels, and school, church, hospital, park and playground locations. These data were used as inputs for exploratory spatial analysis to estimate the expected number of outlets that would eventually operate in Philadelphia. Constraints included proximity restrictions (based on current ordinances regulating outlet distribution) of at least 200 feet between alcohol outlets and at least 300 feet between outlets and schools, churches, hospitals, parks and playgrounds. Results Findings suggest that current state policies on alcohol outlet distributions in Philadelphia are loosely enforced, with many areas exhibiting extremely high spatial densities of outlets that violate existing proximity restrictions. The spatial model indicates that an additional 1,115 outlets could open in Philadelphia if privatization was to occur and current proximity ordinances were maintained. Conclusions The study reveals that spatial analytical approaches can function as an excellent tool for contingency-based “what-if” analysis, providing an objective snapshot of potential policy outcomes prior to implementation. In this case, the likely outcome is a tremendous increase in alcohol outlets in Philadelphia, with concomitant negative health, crime and quality of life outcomes that accompany such an increase. PMID:23170899

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan

PubMed Central

Ng, Ka-Chon; Nguyen, Thi Luong

2018-01-01

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover. PMID:29495351

Exploratory and spatial data analysis (EDA-SDA) for determining regional background levels and anomalies of potentially toxic elements in soils from Catorce-Matehuala, Mexico

USGS Publications Warehouse

Chiprés, J.A.; Castro-Larragoitia, J.; Monroy, M.G.

2009-01-01

The threshold between geochemical background and anomalies can be influenced by the methodology selected for its estimation. Environmental evaluations, particularly those conducted in mineralized areas, must consider this when trying to determinate the natural geochemical status of a study area, quantifying human impacts, or establishing soil restoration values for contaminated sites. Some methods in environmental geochemistry incorporate the premise that anomalies (natural or anthropogenic) and background data are characterized by their own probabilistic distributions. One of these methods uses exploratory data analysis (EDA) on regional geochemical data sets coupled with a geographic information system (GIS) to spatially understand the processes that influence the geochemical landscape in a technique that can be called a spatial data analysis (SDA). This EDA-SDA methodology was used to establish the regional background range from the area of Catorce-Matehuala in north-central Mexico. Probability plots of the data, particularly for those areas affected by human activities, show that the regional geochemical background population is composed of smaller subpopulations associated with factors such as soil type and parent material. This paper demonstrates that the EDA-SDA method offers more certainty in defining thresholds between geochemical background and anomaly than a numeric technique, making it a useful tool for regional geochemical landscape analysis and environmental geochemistry studies.

Epidemiological Characteristics and Space-Time Analysis of the 2015 Dengue Outbreak in the Metropolitan Region of Tainan City, Taiwan.

PubMed

Chuang, Ting-Wu; Ng, Ka-Chon; Nguyen, Thi Luong; Chaves, Luis Fernando

2018-02-26

The metropolitan region of Tainan City in southern Taiwan experienced a dengue outbreak in 2015. This manuscript describes basic epidemiological features of this outbreak and uses spatial and temporal analysis tools to understand the spread of dengue during the outbreak. The analysis found that, independently of gender, dengue incidence rate increased with age, and proportionally affected more males below the age of 40 years but females above the age of 40 years. A spatial scan statistic was applied to detect clusters of disease transmission. The scan statistic found that dengue spread in a north-south diffusion direction, which is across the North, West-Central and South districts of Tainan City. Spatial regression models were used to quantify factors associated with transmission. This analysis indicated that neighborhoods with high proportions of residential area (or low wetland cover) were associated with dengue transmission. However, these association patterns were non-linear. The findings presented here can help Taiwanese public health agencies to understand the fundamental epidemiological characteristics and diffusion patterns of the 2015 dengue outbreak in Tainan City. This type of information is fundamental for policy making to prevent future uncontrolled dengue outbreaks, given that results from this study suggest that control interventions should be emphasized in the North and West-Central districts of Tainan city, in areas with a moderate percentage of residential land cover.

Arrhythmia Mechanism and Scaling Effect on the Spectral Properties of Electroanatomical Maps With Manifold Harmonics.

PubMed

Sanroman-Junquera, Margarita; Mora-Jimenez, Inmaculada; Garcia-Alberola, Arcadio; Caamano, Antonio J; Trenor, Beatriz; Rojo-Alvarez, Jose L

2018-04-01

Spatial and temporal processing of intracardiac electrograms provides relevant information to support the arrhythmia ablation during electrophysiological studies. Current cardiac navigation systems (CNS) and electrocardiographic imaging (ECGI) build detailed 3-D electroanatomical maps (EAM), which represent the spatial anatomical distribution of bioelectrical features, such as activation time or voltage. We present a principled methodology for spectral analysis of both EAM geometry and bioelectrical feature in CNS or ECGI, including their spectral representation, cutoff frequency, or spatial sampling rate (SSR). Existing manifold harmonic techniques for spectral mesh analysis are adapted to account for a fourth dimension, corresponding to the EAM bioelectrical feature. Appropriate scaling is required to address different magnitudes and units. With our approach, simulated and real EAM showed strong SSR dependence on both the arrhythmia mechanism and the cardiac anatomical shape. For instance, high frequencies increased significantly the SSR because of the "early-meets-late" in flutter EAM, compared with the sinus rhythm. Besides, higher frequency components were obtained for the left atrium (more complex anatomy) than for the right atrium in sinus rhythm. The proposed manifold harmonics methodology opens the field toward new signal processing tools for principled EAM spatiofeature analysis in CNS and ECGI, and to an improved knowledge on arrhythmia mechanisms.

Drought assessment using a TRMM-derived standardized precipitation index for the upper São Francisco River basin, Brazil.

PubMed

Santos, Celso Augusto Guimarães; Brasil Neto, Reginaldo Moura; Passos, Jacqueline Sobral de Araújo; da Silva, Richarde Marques

2017-06-01

In this work, the use of Tropical Rainfall Measuring Mission (TRMM) rainfall data and the Standardized Precipitation Index (SPI) for monitoring spatial and temporal drought variabilities in the Upper São Francisco River basin is investigated. Thus, the spatiotemporal behavior of droughts and cluster regions with similar behaviors is identified. As a result, the joint analysis of clusters, dendrograms, and the spatial distribution of SPI values proved to be a powerful tool in identifying homogeneous regions. The results showed that the northeast region of the basin has the lowest rainfall indices and the southwest region has the highest rainfall depths, and that the region has well-defined dry and rainy seasons from June to August and November to January, respectively. An analysis of the drought and rain conditions showed that the studied region was homogeneous and well-distributed; however, the quantity of extreme and severe drought events in short-, medium- and long-term analysis was higher than that expected in regions with high rainfall depths, particularly in the south/southwest and southeast areas. Thus, an alternative classification is proposed to characterize the drought, which spatially categorizes the drought type (short-, medium-, and long-term) according to the analyzed drought event type (extreme, severe, moderate, and mild).

The Ability of Young Korean Children to Use Spatial Representations

ERIC Educational Resources Information Center

Kim, Minsung; Bednarz, Robert; Kim, Jaeyil

2012-01-01

The National Research Council emphasizes using tools of representation as an essential element of spatial thinking. However, it is debatable at what age the use of spatial representation for spatial thinking skills should begin. This study investigated whether young Korean children possess the potential to understand map-like representation using…

Knickpoint finder: A software tool that improves neotectonic analysis

NASA Astrophysics Data System (ADS)

Queiroz, G. L.; Salamuni, E.; Nascimento, E. R.

2015-03-01

This work presents a new software tool for morphometric analysis of drainage networks based on the methods of Hack (1973) and Etchebehere et al. (2004). This tool is applicable to studies of morphotectonics and neotectonics. The software used a digital elevation model (DEM) to identify the relief breakpoints along drainage profiles (knickpoints). The program was coded in Python for use on the ArcGIS platform and is called Knickpoint Finder. A study area was selected to test and evaluate the software's ability to analyze and identify neotectonic morphostructures based on the morphology of the terrain. For an assessment of its validity, we chose an area of the James River basin, which covers most of the Piedmont area of Virginia (USA), which is an area of constant intraplate seismicity and non-orogenic active tectonics and exhibits a relatively homogeneous geodesic surface currently being altered by the seismogenic features of the region. After using the tool in the chosen area, we found that the knickpoint locations are associated with the geologic structures, epicenters of recent earthquakes, and drainages with rectilinear anomalies. The regional analysis demanded the use of a spatial representation of the data after processing using Knickpoint Finder. The results were satisfactory in terms of the correlation of dense areas of knickpoints with active lineaments and the rapidity of the identification of deformed areas. Therefore, this software tool may be considered useful in neotectonic analyses of large areas and may be applied to any area where there is DEM coverage.

An augmented reality tool for learning spatial anatomy on mobile devices.

PubMed

Jain, Nishant; Youngblood, Patricia; Hasel, Matthew; Srivastava, Sakti

2017-09-01

Augmented Realty (AR) offers a novel method of blending virtual and real anatomy for intuitive spatial learning. Our first aim in the study was to create a prototype AR tool for mobile devices. Our second aim was to complete a technical evaluation of our prototype AR tool focused on measuring the system's ability to accurately render digital content in the real world. We imported Computed Tomography (CT) data derived virtual surface models into a 3D Unity engine environment and implemented an AR algorithm to display these on mobile devices. We investigated the accuracy of the virtual renderings by comparing a physical cube with an identical virtual cube for dimensional accuracy. Our comparative study confirms that our AR tool renders 3D virtual objects with a high level of accuracy as evidenced by the degree of similarity between measurements of the dimensions of a virtual object (a cube) and the corresponding physical object. We developed an inexpensive and user-friendly prototype AR tool for mobile devices that creates highly accurate renderings. This prototype demonstrates an intuitive, portable, and integrated interface for spatial interaction with virtual anatomical specimens. Integrating this AR tool with a library of CT derived surface models provides a platform for spatial learning in the anatomy curriculum. The segmentation methodology implemented to optimize human CT data for mobile viewing can be extended to include anatomical variations and pathologies. The ability of this inexpensive educational platform to deliver a library of interactive, 3D models to students worldwide demonstrates its utility as a supplemental teaching tool that could greatly benefit anatomical instruction. Clin. Anat. 30:736-741, 2017. © 2017Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

Tools to Analyze Morphology and Spatially Mapped Molecular Data | Informatics Technology for Cancer Research (ITCR)

Cancer.gov

This project is to develop, deploy, and disseminate a suite of open source tools and integrated informatics platform that will facilitate multi-scale, correlative analyses of high resolution whole slide tissue image data, spatially mapped genetics and molecular data for cancer research. This platform will play an essential role in supporting studies of tumor initiation, development, heterogeneity, invasion, and metastasis.

Spatial and temporal study of nitrate concentration in groundwater by means of coregionalization

USGS Publications Warehouse

D'Agostino, V.; Greene, E.A.; Passarella, G.; Vurro, M.

1998-01-01

Spatial and temporal behavior of hydrochemical parameters in groundwater can be studied using tools provided by geostatistics. The cross-variogram can be used to measure the spatial increments between observations at two given times as a function of distance (spatial structure). Taking into account the existence of such a spatial structure, two different data sets (sampled at two different times), representing concentrations of the same hydrochemical parameter, can be analyzed by cokriging in order to reduce the uncertainty of the estimation. In particular, if one of the two data sets is a subset of the other (that is, an undersampled set), cokriging allows us to study the spatial distribution of the hydrochemical parameter at that time, while also considering the statistical characteristics of the full data set established at a different time. This paper presents an application of cokriging by using temporal subsets to study the spatial distribution of nitrate concentration in the aquifer of the Lucca Plain, central Italy. Three data sets of nitrate concentration in groundwater were collected during three different periods in 1991. The first set was from 47 wells, but the second and the third are undersampled and represent 28 and 27 wells, respectively. Comparing the result of cokriging with ordinary kriging showed an improvement of the uncertainty in terms of reducing the estimation variance. The application of cokriging to the undersampled data sets reduced the uncertainty in estimating nitrate concentration and at the same time decreased the cost of the field sampling and laboratory analysis.Spatial and temporal behavior of hydrochemical parameters in groundwater can be studied using tools provided by geostatistics. The cross-variogram can be used to measure the spatial increments between observations at two given times as a function of distance (spatial structure). Taking into account the existence of such a spatial structure, two different data sets (sampled at two different times), representing concentrations of the same hydrochemical parameter, can be analyzed by cokriging in order to reduce the uncertainty of the estimation. In particular, if one of the two data sets is a subset of the other (that is, an undersampled set), cokriging allows us to study the spatial distribution of the hydrochemical parameter at that time, while also considering the statistical characteristics of the full data set established at a different time. This paper presents an application of cokriging by using temporal subsets to study the spatial distribution of nitrate concentration in the aquifer of the Lucca Plain, central Italy. Three data sets of nitrate concentration in groundwater were collected during three different periods in 1991. The first set was from 47 wells, but the second and the third are undersampled and represent 28 and 27 wells, respectively. Comparing the result of cokriging with ordinary kriging showed an improvement of the uncertainty in terms of reducing the estimation variance. The application of cokriging to the undersampled data sets reduced the uncertainty in estimating nitrate concentration and at the same time decreased the cost of the field sampling and laboratory analysis.

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

PubMed

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

2012-09-01

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

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

NASA Astrophysics Data System (ADS)

Huang, X.; Tan, J.

2014-11-01

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

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

Prioritizing landscapes for longleaf pine conservation

USGS Publications Warehouse

Grand, James B.; Kleiner, Kevin J.

2016-01-01

We developed a spatially explicit model and map, as a decision support tool (DST), to aid conservation agencies creating or maintaining open pine ecosystems. The tool identified areas that are likely to provide the greatest benefit to focal bird populations based on a comprehensive landscape analysis. We used NLCD 2011, SSURGO, and SEGAP data to map the density of desired resources for open pine ecosystems and six focal species of birds and 2 reptiles within the historic range of longleaf pine east of the Mississippi River. Binary rasters were created of sites with desired characteristics such as land form, hydrology, land use and land cover, soils, potential habitat for focal species, and putative source populations of focal species. Each raster was smoothed using a kernel density estimator. Rasters were combined and scaled to map priority locations for the management of each focal species. Species’ rasters were combined and scaled to provide maps of overall priority for birds and for birds and reptiles. The spatial data can be used to identify high priority areas for conservation or to compare areas under consideration for maintenance or creation of open pine ecosystems.

Spatial-temporal consistency between gross primary productivity and solar-induced chlorophyll fluorescence of vegetation in China during 2007-2014

NASA Astrophysics Data System (ADS)

Ma, J.; Xiao, X.; Zhang, Y.; Chen, B.; Zhao, B.

2017-12-01

Great significance exists in accurately estimating spatial-temporal patterns of gross primary production (GPP) because of its important role in global carbon cycle. Satellite-based light use efficiency (LUE) models are regarded as an efficient tool in simulating spatially time-sires GPP. However, the estimation of the accuracy of GPP simulations from LUE at both spatial and temporal scales is still a challenging work. In this study, we simulated GPP of vegetation in China during 2007-2014 using a LUE model (Vegetation Photosynthesis Model, VPM) based on MODIS (moderate-resolution imaging spectroradiometer) images of 8-day temporal and 500-m spatial resolutions and NCEP (National Center for Environmental Prediction) climate data. Global Ozone Monitoring Instrument 2 (GOME-2) solar-induced chlorophyll fluorescence (SIF) data were used to compare with VPM simulated GPP (GPPVPM) temporally and spatially using linear correlation analysis. Significant positive linear correlations exist between monthly GPPVPM and SIF data over both single year (2010) and multiple years (2007-2014) in China. Annual GPPVPM is significantly positive correlated with SIF (R2>0.43) spatially for all years during 2007-2014 and all seasons in 2010 (R2>0.37). GPP dynamic trends is high spatial-temporal heterogeneous in China during 2007-2014. The results of this study indicate that GPPVPM is temporally and spatially in line with SIF data, and space-borne SIF data have great potential in validating and parameterizing GPP estimation of LUE-based models.

On Bi-Grid Local Mode Analysis of Solution Techniques for 3-D Euler and Navier-Stokes Equations

NASA Technical Reports Server (NTRS)

Ibraheem, S. O.; Demuren, A. O.

1994-01-01

A procedure is presented for utilizing a bi-grid stability analysis as a practical tool for predicting multigrid performance in a range of numerical methods for solving Euler and Navier-Stokes equations. Model problems based on the convection, diffusion and Burger's equation are used to illustrate the superiority of the bi-grid analysis as a predictive tool for multigrid performance in comparison to the smoothing factor derived from conventional von Neumann analysis. For the Euler equations, bi-grid analysis is presented for three upwind difference based factorizations, namely Spatial, Eigenvalue and Combination splits, and two central difference based factorizations, namely LU and ADI methods. In the former, both the Steger-Warming and van Leer flux-vector splitting methods are considered. For the Navier-Stokes equations, only the Beam-Warming (ADI) central difference scheme is considered. In each case, estimates of multigrid convergence rates from the bi-grid analysis are compared to smoothing factors obtained from single-grid stability analysis. Effects of grid aspect ratio and flow skewness are examined. Both predictions are compared with practical multigrid convergence rates for 2-D Euler and Navier-Stokes solutions based on the Beam-Warming central scheme.

Numerical Uncertainty Quantification for Radiation Analysis Tools

NASA Technical Reports Server (NTRS)

Anderson, Brooke; Blattnig, Steve; Clowdsley, Martha

2007-01-01

Recently a new emphasis has been placed on engineering applications of space radiation analyses and thus a systematic effort of Verification, Validation and Uncertainty Quantification (VV&UQ) of the tools commonly used for radiation analysis for vehicle design and mission planning has begun. There are two sources of uncertainty in geometric discretization addressed in this paper that need to be quantified in order to understand the total uncertainty in estimating space radiation exposures. One source of uncertainty is in ray tracing, as the number of rays increase the associated uncertainty decreases, but the computational expense increases. Thus, a cost benefit analysis optimizing computational time versus uncertainty is needed and is addressed in this paper. The second source of uncertainty results from the interpolation over the dose vs. depth curves that is needed to determine the radiation exposure. The question, then, is what is the number of thicknesses that is needed to get an accurate result. So convergence testing is performed to quantify the uncertainty associated with interpolating over different shield thickness spatial grids.

Creating a spatial multi-criteria decision support system for energy related integrated environmental impact assessment

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

Wanderer, Thomas, E-mail: thomas.wanderer@dlr.de; Herle, Stefan, E-mail: stefan.herle@rwth-aachen.de

2015-04-15

By their spatially very distributed nature, profitability and impacts of renewable energy resources are highly correlated with the geographic locations of power plant deployments. A web-based Spatial Decision Support System (SDSS) based on a Multi-Criteria Decision Analysis (MCDA) approach has been implemented for identifying preferable locations for solar power plants based on user preferences. The designated areas found serve for the input scenario development for a subsequent integrated Environmental Impact Assessment. The capabilities of the SDSS service get showcased for Concentrated Solar Power (CSP) plants in the region of Andalusia, Spain. The resulting spatial patterns of possible power plant sitesmore » are an important input to the procedural chain of assessing impacts of renewable energies in an integrated effort. The applied methodology and the implemented SDSS are applicable for other renewable technologies as well. - Highlights: • The proposed tool facilitates well-founded CSP plant siting decisions. • Spatial MCDA methods are implemented in a WebGIS environment. • GIS-based SDSS can contribute to a modern integrated impact assessment workflow. • The conducted case study proves the suitability of the methodology.« less

Communicating and Evaluating the Causes of Seismicity in Oklahoma Using ArcGIS Online Story Map Web Applications

NASA Astrophysics Data System (ADS)

Justman, D.; Rose, K.; Bauer, J. R.; Miller, R., III; Vasylkivska, V.; Romeo, L.

2016-12-01

ArcGIS Online story maps allows users to communicate complex topics with geospatially enabled stories. This story map web application entitled "Evaluating the Mysteries of Seismicity in Oklahoma" has been employed as part of a broader research effort investigating the relationships between spatiotemporal systems and seismicity to understand the recent increase in seismicity by reviewing literature, exploring, and performing analyses on key datasets. It offers information about the unprecedented increase in seismic events since 2008, earthquake history, the risk to the population, physical mechanisms behind earthquakes, natural and anthropogenic earthquake factors, and individual & cumulative spatial extents of these factors. The cumulative spatial extents for natural, anthropogenic, and all combined earthquake factors were determined using the Cumulative Spatial Impact Layers (CSILs) tool developed at the National Energy Technology Laboratory (NETL). Results show positive correlations between the average number of influences (datasets related to individual factors) and the number of earthquakes for every 100 square mile grid cell in Oklahoma, along with interesting spatial correlations for the individual & cumulative spatial extents of these factors when overlaid with earthquake density and a hotspot analysis for earthquake magnitude from 2010 to 2015.

A GIS-based spatial correlation analysis for ambient air pollution and AECOPD hospitalizations in Jinan, China.

PubMed

Wang, Wenqiao; Ying, Yangyang; Wu, Quanyuan; Zhang, Haiping; Ma, Dedong; Xiao, Wei

2015-03-01

Acute exacerbations of COPD (AECOPD) are important events during disease procedure. AECOPD have negative effect on patients' quality of life, symptoms and lung function, and result in high socioeconomic costs. Though previous studies have demonstrated the significant association between outdoor air pollution and AECOPD hospitalizations, little is known about the spatial relationship utilized a spatial analyzing technique- Geographical Information System (GIS). Using GIS to investigate the spatial association between ambient air pollution and AECOPD hospitalizations in Jinan City, 2009. 414 AECOPD hospitalization cases in Jinan, 2009 were enrolled in our analysis. Monthly concentrations of five monitored air pollutants (NO2, SO2, PM10, O3, CO) during January 2009-December 2009 were provided by Environmental Protection Agency of Shandong Province. Each individual was geocoded in ArcGIS10.0 software. The spatial distribution of five pollutants and the temporal-spatial specific air pollutants exposure level for each individual was estimated by ordinary Kriging model. Spatial autocorrelation (Global Moran's I) was employed to explore the spatial association between ambient air pollutants and AECOPD hospitalizations. A generalized linear model (GLM) using a Poisson distribution with log-link function was used to construct a core model. At residence, concentrations of SO2, PM10, NO2, CO, O3 and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of SO2, PM10, CO, O3, NO2 at residence is 15.88, 13.93, 12.60, 4.02, 2.44 respectively, while at workplace, concentrations of PM10, SO2, O3, CO and AECOPD hospitalization cases showed statistical significant spatially clustered. The Z-score of PM10, SO2, O3, CO at workplace is 11.39, 8.07, 6.10, and 5.08 respectively. After adjusting for potential confounders in the model, only the PM10 concentrations at workplace showed statistical significance, with a 10 μg/m(3) increase of PM10 at workplace associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD. Ambient air pollution is correlated with AECOPD hospitalizations spatially. A 10 μg/m(3) increase of PM10 at workplace was associated with a 7% (95%CI: [3.3%, 10%]) increase of hospitalizations due to AECOPD in Jinan, 2009. As a spatial data processing tool, GIS has novel and great potential on air pollutants exposure assessment and spatial analysis in AECOPD research. Copyright © 2015 Elsevier Ltd. All rights reserved.

Spatial Analysis of HIV Positive Injection Drug Users in San Francisco, 1987 to 2005

PubMed Central

Martinez, Alexis N.; Mobley, Lee R.; Lorvick, Jennifer; Novak, Scott P.; Lopez, Andrea M.; Kral, Alex H.

2014-01-01

Spatial analyses of HIV/AIDS related outcomes are growing in popularity as a tool to understand geographic changes in the epidemic and inform the effectiveness of community-based prevention and treatment programs. The Urban Health Study was a serial, cross-sectional epidemiological study of injection drug users (IDUs) in San Francisco between 1987 and 2005 (N = 29,914). HIV testing was conducted for every participant. Participant residence was geocoded to the level of the United States Census tract for every observation in dataset. Local indicator of spatial autocorrelation (LISA) tests were used to identify univariate and bivariate Census tract clusters of HIV positive IDUs in two time periods. We further compared three tract level characteristics (% poverty, % African Americans, and % unemployment) across areas of clustered and non-clustered tracts. We identified significant spatial clustering of high numbers of HIV positive IDUs in the early period (1987–1995) and late period (1996–2005). We found significant bivariate clusters of Census tracts where HIV positive IDUs and tract level poverty were above average compared to the surrounding areas. Our data suggest that poverty, rather than race, was an important neighborhood characteristic associated with the spatial distribution of HIV in SF and its spatial diffusion over time. PMID:24722543

Space-time airborne disease mapping applied to detect specific behaviour of varicella in Valencia, Spain.

PubMed

Iftimi, Adina; Montes, Francisco; Santiyán, Ana Míguez; Martínez-Ruiz, Francisco

2015-01-01

Airborne diseases are one of humanity's most feared sicknesses and have regularly caused concern among specialists. Varicella is an airborne disease which usually affects children before the age of 10. Because of its nature, varicella gives rise to interesting spatial, temporal and spatio-temporal patterns. This paper studies spatio-temporal exploratory analysis tools to detect specific behaviour of varicella in the city of Valencia, Spain, from 2008 to 2013. These methods have shown a significant association between the spatial and the temporal component, confirmed by the space-time models applied to the data. High relative risk of varicella is observed in economically disadvantaged regions, areas less involved in vaccination programmes. Copyright © 2015 Elsevier Ltd. All rights reserved.

A Voronoi interior adjacency-based approach for generating a contour tree

NASA Astrophysics Data System (ADS)

Chen, Jun; Qiao, Chaofei; Zhao, Renliang

2004-05-01

A contour tree is a good graphical tool for representing the spatial relations of contour lines and has found many applications in map generalization, map annotation, terrain analysis, etc. A new approach for generating contour trees by introducing a Voronoi-based interior adjacency set concept is proposed in this paper. The immediate interior adjacency set is employed to identify all of the children contours of each contour without contour elevations. It has advantages over existing methods such as the point-in-polygon method and the region growing-based method. This new approach can be used for spatial data mining and knowledge discovering, such as the automatic extraction of terrain features and construction of multi-resolution digital elevation model.

Water Quality Analysis Tool (WQAT) | Science Inventory | US ...

EPA Pesticide Factsheets

The purpose of the Water Quality Analysis Tool (WQAT) software is to provide a means for analyzing and producing useful remotely sensed data products for an entire estuary, a particular point or area of interest (AOI or POI) in estuaries, or water bodies of interest where pre-processed and geographically gridded remotely sensed images are available. A graphical user interface (GUI), was created to enable the user to select and display imagery from a variety of remote sensing data sources. The user can select a date (or date range) and location to extract pixels from the remotely sensed imagery. The GUI is used to obtain all available pixel values (i.e. pixel from all available bands of all available satellites) for a given location on a given date and time. The resultant data set can be analyzed or saved to a file for future use. The WQAT software provides users with a way to establish algorithms between remote sensing reflectance (Rrs) and any available in situ parameters, as well as statistical and regression analysis. The combined data sets can be used to improve water quality research and studies. Satellites provide spatially synoptic data at high frequency (daily to weekly). These characteristics are desirable for supplementing existing water quality observations and for providing information for large aquatic ecosystems that are historically under-sampled by field programs. Thus, the Water Quality Assessment Tool (WQAT) software tool was developed to suppo

Low-loss electron energy loss spectroscopy: An atomic-resolution complement to optical spectroscopies and application to graphene

DOE PAGES

Kapetanakis, Myron; Zhou, Wu; Oxley, Mark P.; ...

2015-09-25

Photon-based spectroscopies have played a central role in exploring the electronic properties of crystalline solids and thin films. They are a powerful tool for probing the electronic properties of nanostructures, but they are limited by lack of spatial resolution. On the other hand, electron-based spectroscopies, e.g., electron energy loss spectroscopy (EELS), are now capable of subangstrom spatial resolution. Core-loss EELS, a spatially resolved analog of x-ray absorption, has been used extensively in the study of inhomogeneous complex systems. In this paper, we demonstrate that low-loss EELS in an aberration-corrected scanning transmission electron microscope, which probes low-energy excitations, combined with amore » theoretical framework for simulating and analyzing the spectra, is a powerful tool to probe low-energy electron excitations with atomic-scale resolution. The theoretical component of the method combines density functional theory–based calculations of the excitations with dynamical scattering theory for the electron beam. We apply the method to monolayer graphene in order to demonstrate that atomic-scale contrast is inherent in low-loss EELS even in a perfectly periodic structure. The method is a complement to optical spectroscopy as it probes transitions entailing momentum transfer. The theoretical analysis identifies the spatial and orbital origins of excitations, holding the promise of ultimately becoming a powerful probe of the structure and electronic properties of individual point and extended defects in both crystals and inhomogeneous complex nanostructures. The method can be extended to probe magnetic and vibrational properties with atomic resolution.« less

Application of dynamic Monte Carlo technique in proton beam radiotherapy using Geant4 simulation toolkit

NASA Astrophysics Data System (ADS)

Guan, Fada

Monte Carlo method has been successfully applied in simulating the particles transport problems. Most of the Monte Carlo simulation tools are static and they can only be used to perform the static simulations for the problems with fixed physics and geometry settings. Proton therapy is a dynamic treatment technique in the clinical application. In this research, we developed a method to perform the dynamic Monte Carlo simulation of proton therapy using Geant4 simulation toolkit. A passive-scattering treatment nozzle equipped with a rotating range modulation wheel was modeled in this research. One important application of the Monte Carlo simulation is to predict the spatial dose distribution in the target geometry. For simplification, a mathematical model of a human body is usually used as the target, but only the average dose over the whole organ or tissue can be obtained rather than the accurate spatial dose distribution. In this research, we developed a method using MATLAB to convert the medical images of a patient from CT scanning into the patient voxel geometry. Hence, if the patient voxel geometry is used as the target in the Monte Carlo simulation, the accurate spatial dose distribution in the target can be obtained. A data analysis tool---root was used to score the simulation results during a Geant4 simulation and to analyze the data and plot results after simulation. Finally, we successfully obtained the accurate spatial dose distribution in part of a human body after treating a patient with prostate cancer using proton therapy.

Evaluation of the effectiveness of 3D vascular stereoscopic models in anatomy instruction for first year medical students.

PubMed

Cui, Dongmei; Wilson, Timothy D; Rockhold, Robin W; Lehman, Michael N; Lynch, James C

2017-01-01

The head and neck region is one of the most complex areas featured in the medical gross anatomy curriculum. The effectiveness of using three-dimensional (3D) models to teach anatomy is a topic of much discussion in medical education research. However, the use of 3D stereoscopic models of the head and neck circulation in anatomy education has not been previously studied in detail. This study investigated whether 3D stereoscopic models created from computed tomographic angiography (CTA) data were efficacious teaching tools for the head and neck vascular anatomy. The test subjects were first year medical students at the University of Mississippi Medical Center. The assessment tools included: anatomy knowledge tests (prelearning session knowledge test and postlearning session knowledge test), mental rotation tests (spatial ability; presession MRT and postsession MRT), and a satisfaction survey. Results were analyzed using a Wilcoxon rank-sum test and linear regression analysis. A total of 39 first year medical students participated in the study. The results indicated that all students who were exposed to the stereoscopic 3D vascular models in 3D learning sessions increased their ability to correctly identify the head and neck vascular anatomy. Most importantly, for students with low-spatial ability, 3D learning sessions improved postsession knowledge scores to a level comparable to that demonstrated by students with high-spatial ability indicating that the use of 3D stereoscopic models may be particularly valuable to these students with low-spatial ability. Anat Sci Educ 10: 34-45. © 2016 American Association of Anatomists. © 2016 American Association of Anatomists.

An integrated user-friendly ArcMAP tool for bivariate statistical modeling in geoscience applications

NASA Astrophysics Data System (ADS)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusof, Z.; Tehrany, M. S.

2014-10-01

Modeling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modeling. Bivariate statistical analysis (BSA) assists in hazard modeling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, BSM (bivariate statistical modeler), for BSA technique is proposed. Three popular BSA techniques such as frequency ratio, weights-of-evidence, and evidential belief function models are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and is created by a simple graphical user interface, which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

An integrated user-friendly ArcMAP tool for bivariate statistical modelling in geoscience applications

NASA Astrophysics Data System (ADS)

Jebur, M. N.; Pradhan, B.; Shafri, H. Z. M.; Yusoff, Z. M.; Tehrany, M. S.

2015-03-01

Modelling and classification difficulties are fundamental issues in natural hazard assessment. A geographic information system (GIS) is a domain that requires users to use various tools to perform different types of spatial modelling. Bivariate statistical analysis (BSA) assists in hazard modelling. To perform this analysis, several calculations are required and the user has to transfer data from one format to another. Most researchers perform these calculations manually by using Microsoft Excel or other programs. This process is time-consuming and carries a degree of uncertainty. The lack of proper tools to implement BSA in a GIS environment prompted this study. In this paper, a user-friendly tool, bivariate statistical modeler (BSM), for BSA technique is proposed. Three popular BSA techniques, such as frequency ratio, weight-of-evidence (WoE), and evidential belief function (EBF) models, are applied in the newly proposed ArcMAP tool. This tool is programmed in Python and created by a simple graphical user interface (GUI), which facilitates the improvement of model performance. The proposed tool implements BSA automatically, thus allowing numerous variables to be examined. To validate the capability and accuracy of this program, a pilot test area in Malaysia is selected and all three models are tested by using the proposed program. Area under curve (AUC) is used to measure the success rate and prediction rate. Results demonstrate that the proposed program executes BSA with reasonable accuracy. The proposed BSA tool can be used in numerous applications, such as natural hazard, mineral potential, hydrological, and other engineering and environmental applications.

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 (...

Exposing ecological and economic costs of the research-implementation gap and compromises in decision making.

PubMed

Kareksela, Santtu; Moilanen, Atte; Ristaniemi, Olli; Välivaara, Reima; Kotiaho, Janne S

2018-02-01

The frequently discussed gap between conservation science and practice is manifest in the gap between spatial conservation prioritization plans and their implementation. We analyzed the research-implementation gap of one zoning case by comparing results of a spatial prioritization analysis aimed at avoiding ecological impact of peat mining in a regional zoning process with the final zoning plan. We examined the relatively complex planning process to determine the gaps among research, zoning, and decision making. We quantified the ecological costs of the differing trade-offs between ecological and socioeconomic factors included in the different zoning suggestions by comparing the landscape-level loss of ecological features (species occurrences, habitat area, etc.) between the different solutions for spatial allocation of peat mining. We also discussed with the scientists and planners the reasons for differing zoning suggestions. The implemented plan differed from the scientists suggestion in that its focus was individual ecological features rather than all the ecological features for which there were data; planners and decision makers considered effects of peat mining on areas not included in the prioritization analysis; zoning was not truly seen as a resource-allocation process and not emphasized in general minimizing ecological losses while satisfying economic needs (peat-mining potential); and decision makers based their prioritization of sites on site-level information showing high ecological value and on single legislative factors instead of finding a cost-effective landscape-level solution. We believe that if the zoning and decision-making processes are very complex, then the usefulness of science-based prioritization tools is likely to be reduced. Nevertheless, we found that high-end tools were useful in clearly exposing trade-offs between conservation and resource utilization. © 2017 Society for Conservation Biology.

Nanopipettes: probes for local sample analysis.

PubMed

Saha-Shah, Anumita; Weber, Anna E; Karty, Jonathan A; Ray, Steven J; Hieftje, Gary M; Baker, Lane A

2015-06-01

Nanopipettes (pipettes with diameters <1 μm) were explored as pressure-driven fluid manipulation tools for sampling nanoliter volumes of fluids. The fundamental behavior of fluids confined in the narrow channels of the nanopipette shank was studied to optimize sampling volume and probe geometry. This method was utilized to collect nanoliter volumes (<10 nL) of sample from single Allium cepa cells and live Drosophila melanogaster first instar larvae. Matrix assisted laser desorption/ionization-mass spectrometry (MALDI-MS) was utilized to characterize the collected sample. The use of nanopipettes for surface sampling of mouse brain tissue sections was also explored. Lipid analyses were performed on mouse brain tissues with spatial resolution of sampling as small as 50 μm. Nanopipettes were shown to be a versatile tool that will find further application in studies of sample heterogeneity and population analysis for a wide range of samples.

Predicting space telerobotic operator training performance from human spatial ability assessment

NASA Astrophysics Data System (ADS)

Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

2013-11-01

Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

Interactive 3D visualization for theoretical virtual observatories

NASA Astrophysics Data System (ADS)

Dykes, T.; Hassan, A.; Gheller, C.; Croton, D.; Krokos, M.

2018-06-01

Virtual observatories (VOs) are online hubs of scientific knowledge. They encompass a collection of platforms dedicated to the storage and dissemination of astronomical data, from simple data archives to e-research platforms offering advanced tools for data exploration and analysis. Whilst the more mature platforms within VOs primarily serve the observational community, there are also services fulfilling a similar role for theoretical data. Scientific visualization can be an effective tool for analysis and exploration of data sets made accessible through web platforms for theoretical data, which often contain spatial dimensions and properties inherently suitable for visualization via e.g. mock imaging in 2D or volume rendering in 3D. We analyse the current state of 3D visualization for big theoretical astronomical data sets through scientific web portals and virtual observatory services. We discuss some of the challenges for interactive 3D visualization and how it can augment the workflow of users in a virtual observatory context. Finally we showcase a lightweight client-server visualization tool for particle-based data sets, allowing quantitative visualization via data filtering, highlighting two example use cases within the Theoretical Astrophysical Observatory.

A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients.

PubMed

Götz, Th I; Lahmer, G; Strnad, V; Bert, Ch; Hensel, B; Tomé, A M; Lang, E W

2017-01-01

During High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient's anatomy, from an initial X-ray-CT-image. During the irradiation treatment, catheter displacements can occur due to patient movements. The current study develops an automatic analysis tool of EMT data sets recorded with a solenoid sensor to assure concordance of the source movement with the treatment plan. The tool combines machine learning techniques such as multi-dimensional scaling (MDS), ensemble empirical mode decomposition (EEMD), singular spectrum analysis (SSA) and particle filter (PF) to precisely detect and quantify any mismatch between the treatment plan and actual EMT measurements. We demonstrate that movement artifacts as well as technical signal distortions can be removed automatically and reliably, resulting in artifact-free reconstructed signals. This is a prerequisite for a highly accurate determination of any deviations of dwell positions from the treatment plan.

A tool to automatically analyze electromagnetic tracking data from high dose rate brachytherapy of breast cancer patients

PubMed Central

Lahmer, G.; Strnad, V.; Bert, Ch.; Hensel, B.; Tomé, A. M.; Lang, E. W.

2017-01-01

During High Dose Rate Brachytherapy (HDR-BT) the spatial position of the radiation source inside catheters implanted into a female breast is determined via electromagnetic tracking (EMT). Dwell positions and dwell times of the radiation source are established, relative to the patient’s anatomy, from an initial X-ray-CT-image. During the irradiation treatment, catheter displacements can occur due to patient movements. The current study develops an automatic analysis tool of EMT data sets recorded with a solenoid sensor to assure concordance of the source movement with the treatment plan. The tool combines machine learning techniques such as multi-dimensional scaling (MDS), ensemble empirical mode decomposition (EEMD), singular spectrum analysis (SSA) and particle filter (PF) to precisely detect and quantify any mismatch between the treatment plan and actual EMT measurements. We demonstrate that movement artifacts as well as technical signal distortions can be removed automatically and reliably, resulting in artifact-free reconstructed signals. This is a prerequisite for a highly accurate determination of any deviations of dwell positions from the treatment plan. PMID:28934238

Analysis and visualization of single-trial event-related potentials

NASA Technical Reports Server (NTRS)

Jung, T. P.; Makeig, S.; Westerfield, M.; Townsend, J.; Courchesne, E.; Sejnowski, T. J.

2001-01-01

In this study, a linear decomposition technique, independent component analysis (ICA), is applied to single-trial multichannel EEG data from event-related potential (ERP) experiments. Spatial filters derived by ICA blindly separate the input data into a sum of temporally independent and spatially fixed components arising from distinct or overlapping brain or extra-brain sources. Both the data and their decomposition are displayed using a new visualization tool, the "ERP image," that can clearly characterize single-trial variations in the amplitudes and latencies of evoked responses, particularly when sorted by a relevant behavioral or physiological variable. These tools were used to analyze data from a visual selective attention experiment on 28 control subjects plus 22 neurological patients whose EEG records were heavily contaminated with blink and other eye-movement artifacts. Results show that ICA can separate artifactual, stimulus-locked, response-locked, and non-event-related background EEG activities into separate components, a taxonomy not obtained from conventional signal averaging approaches. This method allows: (1) removal of pervasive artifacts of all types from single-trial EEG records, (2) identification and segregation of stimulus- and response-locked EEG components, (3) examination of differences in single-trial responses, and (4) separation of temporally distinct but spatially overlapping EEG oscillatory activities with distinct relationships to task events. The proposed methods also allow the interaction between ERPs and the ongoing EEG to be investigated directly. We studied the between-subject component stability of ICA decomposition of single-trial EEG epochs by clustering components with similar scalp maps and activation power spectra. Components accounting for blinks, eye movements, temporal muscle activity, event-related potentials, and event-modulated alpha activities were largely replicated across subjects. Applying ICA and ERP image visualization to the analysis of sets of single trials from event-related EEG (or MEG) experiments can increase the information available from ERP (or ERF) data. Copyright 2001 Wiley-Liss, Inc.

Mapping for the management of diffuse pollution risks related to agricultural plant protection practices: case of the Etang de l'Or catchment area in France.

PubMed

Mghirbi, Oussama; Bord, Jean-Paul; Le Grusse, Philippe; Mandart, Elisabeth; Fabre, Jacques

2018-03-08

Faced with health, environmental, and socio-economic issues related to the heavy use of pesticides, diffuse phytosanitary pollution becomes a major concern shared by all the field actors. These actors, namely the farmers and territorial managers, have expressed the need to implement decision support tools for the territorial management of diffuse pollution resulting from the plant protection practices and their impacts. To meet these steadily increasing requests, a cartographic analysis approach was implemented based on GIS which allows the spatialization of the diffuse pollution impacts related to plant protection practices on the Etang de l'Or catchment area in the South of France. Risk mapping represents a support-decision tool that enables the different field actors to identify and locate vulnerable areas, so as to determine action plans and agri-environmental measures depending on the context of the natural environment. This work shows that mapping is helpful for managing risks related to the use of pesticides in agriculture by employing indicators of pressure (TFI) and risk on the applicator's health (IRSA) and on the environment (IRTE). These indicators were designed to assess the impact of plant protection practices at various spatial scales (field, farm, etc.). The cartographic analysis of risks related to plant protection practices shows that diffuse pollution is unequally located in the North (known for its abundant garrigues and vineyards) and in the South of the Etang de l'Or catchment area (the Mauguio-Lunel agricultural plain known for its diversified cropping systems). This spatial inequity is essentially related to land use and agricultural production system. Indeed, the agricultural lands cover about 60% of the total catchment area. Consequently, this cartographic analysis helps the territorial actors with the implementation of strategies for managing risks of diffuse pollution related to pesticides use in agriculture, based on environmental and socio-economic issues and the characteristics of the natural environment.

A Web Geographic Information System to share data and explorative analysis tools: The application to West Nile disease in the Mediterranean basin.

PubMed

Savini, Lara; Tora, Susanna; Di Lorenzo, Alessio; Cioci, Daniela; Monaco, Federica; Polci, Andrea; Orsini, Massimiliano; Calistri, Paolo; Conte, Annamaria

2018-01-01

In the last decades an increasing number of West Nile Disease cases was observed in equines and humans in the Mediterranean basin and surveillance systems are set up in numerous countries to manage and control the disease. The collection, storage and distribution of information on the spread of the disease becomes important for a shared intervention and control strategy. To this end, a Web Geographic Information System has been developed and disease data, climatic and environmental remote sensed data, full genome sequences of selected isolated strains are made available. This paper describes the Disease Monitoring Dashboard (DMD) web system application, the tools available for the preliminary analysis on climatic and environmental factors and the other interactive tools for epidemiological analysis. WNV occurrence data are collected from multiple official and unofficial sources. Whole genome sequences and metadata of WNV strains are retrieved from public databases or generated in the framework of the Italian surveillance activities. Climatic and environmental data are provided by NASA website. The Geographical Information System is composed by Oracle 10g Database and ESRI ArcGIS Server 10.03; the web mapping client application is developed with the ArcGIS API for Javascript and Phylocanvas library to facilitate and optimize the mash-up approach. ESRI ArcSDE 10.1 has been used to store spatial data. The DMD application is accessible through a generic web browser at https://netmed.izs.it/networkMediterraneo/. The system collects data through on-line forms and automated procedures and visualizes data as interactive graphs, maps and tables. The spatial and temporal dynamic visualization of disease events is managed by a time slider that returns results on both map and epidemiological curve. Climatic and environmental data can be associated to cases through python procedures and downloaded as Excel files. The system compiles multiple datasets through user-friendly web tools; it integrates entomological, veterinary and human surveillance, molecular information on pathogens and environmental and climatic data. The principal result of the DMD development is the transfer and dissemination of knowledge and technologies to develop strategies for integrated prevention and control measures of animal and human diseases.

Extracting microtubule networks from superresolution single-molecule localization microscopy data

PubMed Central

Zhang, Zhen; Nishimura, Yukako; Kanchanawong, Pakorn

2017-01-01

Microtubule filaments form ubiquitous networks that specify spatial organization in cells. However, quantitative analysis of microtubule networks is hampered by their complex architecture, limiting insights into the interplay between their organization and cellular functions. Although superresolution microscopy has greatly facilitated high-resolution imaging of microtubule filaments, extraction of complete filament networks from such data sets is challenging. Here we describe a computational tool for automated retrieval of microtubule filaments from single-molecule-localization–based superresolution microscopy images. We present a user-friendly, graphically interfaced implementation and a quantitative analysis of microtubule network architecture phenotypes in fibroblasts. PMID:27852898

A proposed metric for assessing the measurement quality of individual microarrays

PubMed Central

Kim, Kyoungmi; Page, Grier P; Beasley, T Mark; Barnes, Stephen; Scheirer, Katherine E; Allison, David B

2006-01-01

Background High-density microarray technology is increasingly applied to study gene expression levels on a large scale. Microarray experiments rely on several critical steps that may introduce error and uncertainty in analyses. These steps include mRNA sample extraction, amplification and labeling, hybridization, and scanning. In some cases this may be manifested as systematic spatial variation on the surface of microarray in which expression measurements within an individual array may vary as a function of geographic position on the array surface. Results We hypothesized that an index of the degree of spatiality of gene expression measurements associated with their physical geographic locations on an array could indicate the summary of the physical reliability of the microarray. We introduced a novel way to formulate this index using a statistical analysis tool. Our approach regressed gene expression intensity measurements on a polynomial response surface of the microarray's Cartesian coordinates. We demonstrated this method using a fixed model and presented results from real and simulated datasets. Conclusion We demonstrated the potential of such a quantitative metric for assessing the reliability of individual arrays. Moreover, we showed that this procedure can be incorporated into laboratory practice as a means to set quality control specifications and as a tool to determine whether an array has sufficient quality to be retained in terms of spatial correlation of gene expression measurements. PMID:16430768

Persistent Scatterer Interferometry subsidence data exploitation using spatial tools: The Vega Media of the Segura River Basin case study

NASA Astrophysics Data System (ADS)

Tomas, R.; Herrera, G.; Cooksley, G.; Mulas, J.

2011-04-01

SummaryThe aim of this paper is to analyze the subsidence affecting the Vega Media of the Segura River Basin, using a Persistent Scatterers Interferometry technique (PSI) named Stable Point Network (SPN). This technique is capable of estimating mean deformation velocity maps of the ground surface and displacement time series from Synthetic Aperture Radar (SAR) images. A dataset acquired between January 2004 and December 2008 from ERS-2 and ENVISAT sensors has been processed measuring maximum subsidence and uplift rates of -25.6 and 7.54 mm/year respectively for the whole area. These data have been validated against ground subsidence measurements and compared with subsidence triggering and conditioning factors by means of a Geographical Information System (GIS). The spatial analysis shows a good relationship between subsidence and piezometric level evolution, pumping wells location, river distance, geology, the Arab wall, previously proposed subsidence predictive model and soil thickness. As a consequence, the paper shows the usefulness and the potential of combining Differential SAR Interferometry (DInSAR) and spatial analysis techniques in order to improve the knowledge of this kind of phenomenon.

Rigidity controllable polishing tool based on magnetorheological effect

NASA Astrophysics Data System (ADS)

Wang, Jia; Wan, Yongjian; Shi, Chunyan

2012-10-01

A stable and predictable material removal function (MRF) plays a crucial role in computer controlled optical surfacing (CCOS). For physical contact polishing case, the stability of MRF depends on intimate contact between polishing interface and workpiece. Rigid laps maintain this function in polishing spherical surfaces, whose curvature has no variation with the position on the surface. Such rigid laps provide smoothing effect for mid-spatial frequency errors, but can't be used in aspherical surfaces for they will destroy the surface figure. Flexible tools such as magnetorheological fluid or air bonnet conform to the surface [1]. They lack rigidity and provide little natural smoothing effect. We present a rigidity controllable polishing tool that uses a kind of magnetorheological elastomers (MRE) medium [2]. It provides the ability of both conforming to the aspheric surface and maintaining natural smoothing effect. What's more, its rigidity can be controlled by the magnetic field. This paper will present the design, analysis, and stiffness variation mechanism model of such polishing tool [3].

Modeling evolution of spatially distributed bacterial communities: a simulation with the haploid evolutionary constructor

PubMed Central

2015-01-01

Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

The Wavelet ToolKat: A set of tools for the analysis of series through wavelet transforms. Application to the channel curvature and the slope control of three free meandering rivers in the Amazon basin.

NASA Astrophysics Data System (ADS)

Vaudor, Lise; Piegay, Herve; Wawrzyniak, Vincent; Spitoni, Marie

2016-04-01

The form and functioning of a geomorphic system result from processes operating at various spatial and temporal scales. Longitudinal channel characteristics thus exhibit complex patterns which vary according to the scale of study, might be periodic or segmented, and are generally blurred by noise. Describing the intricate, multiscale structure of such signals, and identifying at which scales the patterns are dominant and over which sub-reach, could help determine at which scales they should be investigated, and provide insights into the main controlling factors. Wavelet transforms aim at describing data at multiple scales (either in time or space), and are now exploited in geophysics for the analysis of nonstationary series of data. They provide a consistent, non-arbitrary, and multiscale description of a signal's variations and help explore potential causalities. Nevertheless, their use in fluvial geomorphology, notably to study longitudinal patterns, is hindered by a lack of user-friendly tools to help understand, implement, and interpret them. We have developed a free application, The Wavelet ToolKat, designed to facilitate the use of wavelet transforms on temporal or spatial series. We illustrate its usefulness describing longitudinal channel curvature and slope of three freely meandering rivers in the Amazon basin (the Purus, Juruá and Madre de Dios rivers), using topographic data generated from NASA's Shuttle Radar Topography Mission (SRTM) in 2000. Three types of wavelet transforms are used, with different purposes. Continuous Wavelet Transforms are used to identify in a non-arbitrary way the dominant scales and locations at which channel curvature and slope vary. Cross-wavelet transforms, and wavelet coherence and phase are used to identify scales and locations exhibiting significant channel curvature and slope co-variations. Maximal Overlap Discrete Wavelet Transforms decompose data into their variations at a series of scales and are used to provide smoothed descriptions of the series at the scales deemed relevant.

Geographical distribution of human Schistosoma japonicum infection in The Philippines: tools to support disease control and further elimination

PubMed Central

Magalhães, Ricardo J Soares; Salamat, Maria Sonia; Leonardo, Lydia; Gray, Darren J; Carabin, Hélène; Halton, Kate; McManus, Donald P; Williams, Gail M; Rivera, Pilarita; Saniel, Ofelia; Hernandez, Leda; Yakob, Laith; McGarvey, Stephen; Clements, Archie

2015-01-01

Schistosoma japonicum infection is believed to be endemic in 28 of the 80 provinces of The Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small-scale spatial variation in S. japonicum prevalence across The Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geolocated at the barangay level and included in the analysis. The analysis was then stratified geographically for the regions of Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ≥ 20 years had significantly higher prevalence of S. japonicum compared with females and children < 5 years. The role of the environmental variables differed between regions of The Philippines. Schistosoma japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in the prevalence of S. japonicum infection in The Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritized for areas identified to be at high risk but which were under-represented in our dataset. PMID:25128879

Geographical distribution of human Schistosoma japonicum infection in The Philippines: tools to support disease control and further elimination.

PubMed

Soares Magalhães, Ricardo J; Salamat, Maria Sonia; Leonardo, Lydia; Gray, Darren J; Carabin, Hélène; Halton, Kate; McManus, Donald P; Williams, Gail M; Rivera, Pilarita; Saniel, Ofelia; Hernandez, Leda; Yakob, Laith; McGarvey, Stephen; Clements, Archie

2014-11-01

Schistosoma japonicum infection is believed to be endemic in 28 of the 80 provinces of The Philippines and the most recent data on schistosomiasis prevalence have shown considerable variability between provinces. In order to increase the efficient allocation of parasitic disease control resources in the country, we aimed to describe the small-scale spatial variation in S. japonicum prevalence across The Philippines, quantify the role of the physical environment in driving the spatial variation of S. japonicum, and develop a predictive risk map of S. japonicum infection. Data on S. japonicum infection from 35,754 individuals across the country were geo-located at the barangay level and included in the analysis. The analysis was then stratified geographically for the regions of Luzon, the Visayas and Mindanao. Zero-inflated binomial Bayesian geostatistical models of S. japonicum prevalence were developed and diagnostic uncertainty was incorporated. Results of the analysis show that in the three regions, males and individuals aged ⩾20years had significantly higher prevalence of S. japonicum compared with females and children <5years. The role of the environmental variables differed between regions of The Philippines. Schistosoma japonicum infection was widespread in the Visayas whereas it was much more focal in Luzon and Mindanao. This analysis revealed significant spatial variation in the prevalence of S. japonicum infection in The Philippines. This suggests that a spatially targeted approach to schistosomiasis interventions, including mass drug administration, is warranted. When financially possible, additional schistosomiasis surveys should be prioritised for areas identified to be at high risk but which were under-represented in our dataset. Copyright © 2014 Australian Society for Parasitology Inc. Published by Elsevier Ltd. All rights reserved.

A comparison of spatial analysis methods for the construction of topographic maps of retinal cell density.

PubMed

Garza-Gisholt, Eduardo; Hemmi, Jan M; Hart, Nathan S; Collin, Shaun P

2014-01-01

Topographic maps that illustrate variations in the density of different neuronal sub-types across the retina are valuable tools for understanding the adaptive significance of retinal specialisations in different species of vertebrates. To date, such maps have been created from raw count data that have been subjected to only limited analysis (linear interpolation) and, in many cases, have been presented as iso-density contour maps with contour lines that have been smoothed 'by eye'. With the use of stereological approach to count neuronal distribution, a more rigorous approach to analysing the count data is warranted and potentially provides a more accurate representation of the neuron distribution pattern. Moreover, a formal spatial analysis of retinal topography permits a more robust comparison of topographic maps within and between species. In this paper, we present a new R-script for analysing the topography of retinal neurons and compare methods of interpolating and smoothing count data for the construction of topographic maps. We compare four methods for spatial analysis of cell count data: Akima interpolation, thin plate spline interpolation, thin plate spline smoothing and Gaussian kernel smoothing. The use of interpolation 'respects' the observed data and simply calculates the intermediate values required to create iso-density contour maps. Interpolation preserves more of the data but, consequently includes outliers, sampling errors and/or other experimental artefacts. In contrast, smoothing the data reduces the 'noise' caused by artefacts and permits a clearer representation of the dominant, 'real' distribution. This is particularly useful where cell density gradients are shallow and small variations in local density may dramatically influence the perceived spatial pattern of neuronal topography. The thin plate spline and the Gaussian kernel methods both produce similar retinal topography maps but the smoothing parameters used may affect the outcome.

Catchment scale water resource constraints on UK policies for low-carbon energy system transition

NASA Astrophysics Data System (ADS)

Konadu, D. D.; Fenner, R. A.

2017-12-01

Long-term low-carbon energy transition policy of the UK presents national scale propositions of different low-carbon energy system options that lead to meeting GHG emissions reduction target of 80% on 1990 levels by 2050. Whilst national-scale assessments suggests that water availability may not be a significant constrain on future thermal power generation systems in this pursuit, these analysis fail to capture the appropriate spatial scale where water resource decisions are made, i.e. at the catchment scale. Water is a local resource, which also has significant spatio-temporal regional and national variability, thus any policy-relevant water-energy nexus analysis must be reflective of these characteristics. This presents a critical challenge for policy relevant water-energy nexus analysis. This study seeks to overcome the above challenge by using a linear spatial-downscaling model to allocate nationally projected water-intensive energy system infrastructure/technologies to the catchment level, and estimating the water requirements for the deployment of these technologies. The model is applied to the UK Committee on Climate Change Carbon Budgets to 2030 as a case study. The paper concludes that whilst national-scale analyses show minimal long-term water related impacts, catchment level appraisal of water resource requirements reveal significant constraints in some locations. The approach and results presented in this study thus, highlights the importance of bringing together scientific understanding, data and analysis tools to provide better insights for water-energy nexus decisions at the appropriate spatial scale. This is particularly important for water stressed regions where the water-energy nexus must be analysed at appropriate spatial resolution to capture the full water resource impact of national energy policy.

p3d--Python module for structural bioinformatics.

PubMed

Fufezan, Christian; Specht, Michael

2009-08-21

High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files). p3d's strength arises from the combination of a) very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP) tree, b) set theory and c) functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.

PDNAsite: Identification of DNA-binding Site from Protein Sequence by Incorporating Spatial and Sequence Context

PubMed Central

Zhou, Jiyun; Xu, Ruifeng; He, Yulan; Lu, Qin; Wang, Hongpeng; Kong, Bing

2016-01-01

Protein-DNA interactions are involved in many fundamental biological processes essential for cellular function. Most of the existing computational approaches employed only the sequence context of the target residue for its prediction. In the present study, for each target residue, we applied both the spatial context and the sequence context to construct the feature space. Subsequently, Latent Semantic Analysis (LSA) was applied to remove the redundancies in the feature space. Finally, a predictor (PDNAsite) was developed through the integration of the support vector machines (SVM) classifier and ensemble learning. Results on the PDNA-62 and the PDNA-224 datasets demonstrate that features extracted from spatial context provide more information than those from sequence context and the combination of them gives more performance gain. An analysis of the number of binding sites in the spatial context of the target site indicates that the interactions between binding sites next to each other are important for protein-DNA recognition and their binding ability. The comparison between our proposed PDNAsite method and the existing methods indicate that PDNAsite outperforms most of the existing methods and is a useful tool for DNA-binding site identification. A web-server of our predictor (http://hlt.hitsz.edu.cn:8080/PDNAsite/) is made available for free public accessible to the biological research community. PMID:27282833

The effectiveness of physical models in teaching anatomy: a meta-analysis of comparative studies.

PubMed

Yammine, Kaissar; Violato, Claudio

2016-10-01

There are various educational methods used in anatomy teaching. While three dimensional (3D) visualization technologies are gaining ground due to their ever-increasing realism, reports investigating physical models as a low-cost 3D traditional method are still the subject of considerable interest. The aim of this meta-analysis is to quantitatively assess the effectiveness of such models based on comparative studies. Eight studies (7 randomized trials; 1 quasi-experimental) including 16 comparison arms and 820 learners met the inclusion criteria. Primary outcomes were defined as factual, spatial and overall percentage scores. The meta-analytical results are: educational methods using physical models yielded significantly better results when compared to all other educational methods for the overall knowledge outcome (p < 0.001) and for spatial knowledge acquisition (p < 0.001). Significantly better results were also found with regard to the long-retention knowledge outcome (p < 0.01). No significance was found for the factual knowledge acquisition outcome. The evidence in the present systematic review was found to have high internal validity and at least an acceptable strength. In conclusion, physical anatomical models offer a promising tool for teaching gross anatomy in 3D representation due to their easy accessibility and educational effectiveness. Such models could be a practical tool to bring up the learners' level of gross anatomy knowledge at low cost.

Spatial heterogeneity of within-stream methane concentrations

NASA Astrophysics Data System (ADS)

Crawford, John T.; Loken, Luke C.; West, William E.; Crary, Benjamin; Spawn, Seth A.; Gubbins, Nicholas; Jones, Stuart E.; Striegl, Robert G.; Stanley, Emily H.

2017-05-01

Streams, rivers, and other freshwater features may be significant sources of CH4 to the atmosphere. However, high spatial and temporal variabilities hinder our ability to understand the underlying processes of CH4 production and delivery to streams and also challenge the use of scaling approaches across large areas. We studied a stream having high geomorphic variability to assess the underlying scale of CH4 spatial variability and to examine whether the physical structure of a stream can explain the variation in surface CH4. A combination of high-resolution CH4 mapping, a survey of groundwater CH4 concentrations, quantitative analysis of methanogen DNA, and sediment CH4 production potentials illustrates the spatial and geomorphic controls on CH4 emissions to the atmosphere. We observed significant spatial clustering with high CH4 concentrations in organic-rich stream reaches and lake transitions. These sites were also enriched in the methane-producing mcrA gene and had highest CH4 production rates in the laboratory. In contrast, mineral-rich reaches had significantly lower concentrations and had lesser abundances of mcrA. Strong relationships between CH4 and the physical structure of this aquatic system, along with high spatial variability, suggest that future investigations will benefit from viewing streams as landscapes, as opposed to ecosystems simply embedded in larger terrestrial mosaics. In light of such high spatial variability, we recommend that future workers evaluate stream networks first by using similar spatial tools in order to build effective sampling programs.

Analyzing existing conventional soil information sources to be incorporated in thematic Spatial Data Infrastructures

NASA Astrophysics Data System (ADS)

Pascual-Aguilar, J. A.; Rubio, J. L.; Domínguez, J.; Andreu, V.

2012-04-01

New information technologies give the possibility of widespread dissemination of spatial information to different geographical scales from continental to local by means of Spatial Data Infrastructures. Also administrative awareness on the need for open access information services has allowed the citizens access to this spatial information through development of legal documents, such as the INSPIRE Directive of the European Union, adapted by national laws as in the case of Spain. The translation of the general criteria of generic Spatial Data Infrastructures (SDI) to thematic ones is a crucial point for the progress of these instruments as large tool for the dissemination of information. In such case, it must be added to the intrinsic criteria of digital information, such as the harmonization information and the disclosure of metadata, the own environmental information characteristics and the techniques employed in obtaining it. In the case of inventories and mapping of soils, existing information obtained by traditional means, prior to the digital technologies, is considered to be a source of valid information, as well as unique, for the development of thematic SDI. In this work, an evaluation of existing and accessible information that constitutes the basis for building a thematic SDI of soils in Spain is undertaken. This information framework has common features to other European Union states. From a set of more than 1,500 publications corresponding to the national territory of Spain, the study was carried out in those documents (94) found for five autonomous regions of northern Iberian Peninsula (Asturias, Cantabria, Basque Country, Navarra and La Rioja). The analysis was performed taking into account the criteria of soil mapping and inventories. The results obtained show a wide variation in almost all the criteria: geographic representation (projections, scales) and geo-referencing the location of the profiles, map location of profiles integrated with edaphic units, description and taxonomic classification systems of soils (FAO, Soil taxonomy, etc.), amount and type of soil analysis parameters and dates of the inventories. In conclusion, the construction of thematic SDI on soil should take into account, prior to the integration of all maps and inventories, a series of processes of harmonization that allows spatial continuity between existing information and also temporal identification of the inventories and maps. This should require the development of at least two types of integration tools: (1) enabling spatial continuity without contradictions between maps made at different times and with different criteria and (2) the development of information systems data (metadata) to highlight the characteristics of information and connection possibilities with other sources that comprise the Spatial Data Infrastructure. Acknowledgements This research has financed by the European Union within the framework of the GS Soil project (eContentplus Programme ECP-2008-GEO-318004).

Assessment and application of national environmental databases and mapping tools at the local level to two community case studies.

PubMed

Hammond, Davyda; Conlon, Kathryn; Barzyk, Timothy; Chahine, Teresa; Zartarian, Valerie; Schultz, Brad

2011-03-01

Communities are concerned over pollution levels and seek methods to systematically identify and prioritize the environmental stressors in their communities. Geographic information system (GIS) maps of environmental information can be useful tools for communities in their assessment of environmental-pollution-related risks. Databases and mapping tools that supply community-level estimates of ambient concentrations of hazardous pollutants, risk, and potential health impacts can provide relevant information for communities to understand, identify, and prioritize potential exposures and risk from multiple sources. An assessment of existing databases and mapping tools was conducted as part of this study to explore the utility of publicly available databases, and three of these databases were selected for use in a community-level GIS mapping application. Queried data from the U.S. EPA's National-Scale Air Toxics Assessment, Air Quality System, and National Emissions Inventory were mapped at the appropriate spatial and temporal resolutions for identifying risks of exposure to air pollutants in two communities. The maps combine monitored and model-simulated pollutant and health risk estimates, along with local survey results, to assist communities with the identification of potential exposure sources and pollution hot spots. Findings from this case study analysis will provide information to advance the development of new tools to assist communities with environmental risk assessments and hazard prioritization. © 2010 Society for Risk Analysis.

Large High Resolution Displays for Co-Located Collaborative Sensemaking: Display Usage and Territoriality

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

Bradel, Lauren; Endert, Alexander; Koch, Kristen

2013-08-01

Large, high-resolution vertical displays carry the potential to increase the accuracy of collaborative sensemaking, given correctly designed visual analytics tools. From an exploratory user study using a fictional textual intelligence analysis task, we investigated how users interact with the display to construct spatial schemas and externalize information, as well as how they establish shared and private territories. We investigated the space management strategies of users partitioned by type of tool philosophy followed (visualization- or text-centric). We classified the types of territorial behavior exhibited in terms of how the users interacted with information on the display (integrated or independent workspaces). Next,more » we examined how territorial behavior impacted the common ground between the pairs of users. Finally, we offer design suggestions for building future co-located collaborative visual analytics tools specifically for use on large, high-resolution vertical displays.« less

WaveAR: A software tool for calculating parameters for water waves with incident and reflected components

NASA Astrophysics Data System (ADS)

Landry, Blake J.; Hancock, Matthew J.; Mei, Chiang C.; García, Marcelo H.

2012-09-01

The ability to determine wave heights and phases along a spatial domain is vital to understanding a wide range of littoral processes. The software tool presented here employs established Stokes wave theory and sampling methods to calculate parameters for the incident and reflected components of a field of weakly nonlinear waves, monochromatic at first order in wave slope and propagating in one horizontal dimension. The software calculates wave parameters over an entire wave tank and accounts for reflection, weak nonlinearity, and a free second harmonic. Currently, no publicly available program has such functionality. The included MATLAB®-based open source code has also been compiled for Windows®, Mac® and Linux® operating systems. An additional companion program, VirtualWave, is included to generate virtual wave fields for WaveAR. Together, the programs serve as ideal analysis and teaching tools for laboratory water wave systems.

Dressing the Coronal Magnetic Extrapolations of Active Regions with a Parameterized Thermal Structure

NASA Astrophysics Data System (ADS)

Nita, Gelu M.; Viall, Nicholeen M.; Klimchuk, James A.; Loukitcheva, Maria A.; Gary, Dale E.; Kuznetsov, Alexey A.; Fleishman, Gregory D.

2018-01-01

The study of time-dependent solar active region (AR) morphology and its relation to eruptive events requires analysis of imaging data obtained in multiple wavelength domains with differing spatial and time resolution, ideally in combination with 3D physical models. To facilitate this goal, we have undertaken a major enhancement of our IDL-based simulation tool, GX_Simulator, previously developed for modeling microwave and X-ray emission from flaring loops, to allow it to simulate quiescent emission from solar ARs. The framework includes new tools for building the atmospheric model and enhanced routines for calculating emission that include new wavelengths. In this paper, we use our upgraded tool to model and analyze an AR and compare the synthetic emission maps with observations. We conclude that the modeled magneto-thermal structure is a reasonably good approximation of the real one.

Regulating outdoor advertisement boards; employing spatial decision support system to control urban visual pollution

NASA Astrophysics Data System (ADS)

Wakil, K.; Hussnain, MQ; Tahir, A.; Naeem, M. A.

2016-06-01

Unmanaged placement, size, location, structure and contents of outdoor advertisement boards have resulted in severe urban visual pollution and deterioration of the socio-physical living environment in urban centres of Pakistan. As per the regulatory instruments, the approval decision for a new advertisement installation is supposed to be based on the locational density of existing boards and their proximity or remoteness to certain land- uses. In cities, where regulatory tools for the control of advertisement boards exist, responsible authorities are handicapped in effective implementation due to the absence of geospatial analysis capacity. This study presents the development of a spatial decision support system (SDSS) for regularization of advertisement boards in terms of their location and placement. The knowledge module of the proposed SDSS is based on provisions and restrictions prescribed in regulatory documents. While the user interface allows visualization and scenario evaluation to understand if the new board will affect existing linear density on a particular road and if it violates any buffer restrictions around a particular land use. Technically the structure of the proposed SDSS is a web-based solution which includes open geospatial tools such as OpenGeo Suite, GeoExt, PostgreSQL, and PHP. It uses three key data sets including road network, locations of existing billboards and building parcels with land use information to perform the analysis. Locational suitability has been calculated using pairwise comparison through analytical hierarchy process (AHP) and weighted linear combination (WLC). Our results indicate that open geospatial tools can be helpful in developing an SDSS which can assist solving space related iterative decision challenges on outdoor advertisements. Employing such a system will result in effective implementation of regulations resulting in visual harmony and aesthetic improvement in urban communities.

Geographic information systems (GIS): an emerging method to assess demand and provision for rehabilitation services.

PubMed

Passalent, Laura; Borsy, Emily; Landry, Michel D; Cott, Cheryl

2013-09-01

To illustrate the application of geographic information systems (GIS) as a tool to assess rehabilitation service delivery by presenting results from research recently conducted to assess demand and provision for community rehabilitation service delivery in Ontario, Canada. Secondary analysis of data obtained from existing sources was used to establish demand and provision profiles for community rehabilitation services. These data were integrated using GIS software. A number of descriptive maps were produced that show the geographical distribution of service provision variables (location of individual rehabilitation health care providers and location of private and publicly funded community rehabilitation clinics) in relation to the distribution of demand variables (location of the general population; location of specific populations (i.e., residents age 65 and older) and distribution of household income). GIS provides a set of tools for describing and understanding the spatial organization of the health of populations and the distribution of health services that can aid the development of health policy and answer key research questions with respect to rehabilitation health services delivery. Implications for Rehabilitation It is important to seek out alternative and innovative methods to examine rehabilitation service delivery. GIS is a computer-based program that takes any data linked to a geographically referenced location and processes it through a software system that manages, analyses and displays the data in the form of a map, allowing for an alternative level of analysis. GIS provides a set of tools for describing and understanding the spatial organization of population health and health services that can aid the development of health policy and answer key research questions with respect to rehabilitation health services delivery.

Development, application, and sensitivity analysis of a water quality index for drinking water management in small systems.

PubMed

Scheili, A; Rodriguez, Manuel J; Sadiq, R

2015-11-01

The aim of this study was to produce a drinking water assessment tool for operators of small distribution systems. A drinking water quality index (DWQI) was developed and applied to small systems based on the water quality index of the Canadian Council of Ministers of Environment. The drinking water quality index was adapted to specific needs by creating four drinking water quality scenarios. First, the temporal and spatial dimensions of drinking water quality variability were taken into account. The DWQI was designed to express global drinking water quality according to different monitoring frequencies. Daily, monthly, and seasonal assessment was also considered. With the data made available, it was possible to use the index as a spatial monitoring tool and express water quality in different points in the distribution system. Moreover, adjustments were made to prioritize the type of contaminant to monitor. For instance, monitoring contaminants with acute health effects led to a scenario based on daily measures, including easily accessible and affordable water quality parameters. On the other hand, contaminants with chronic effects, especially disinfection by-products, were considered in a seasonal monitoring scenario where disinfection by-product reference values were redefined according to their seasonal variability. A sensitivity analysis was also carried out to validate the index. Globally, the DWQI developed is adapted to the needs of small systems. In fact, expressing drinking water quality using the DWQI contributes to the identification of problematic periods and segments in the distribution system. Further work may include this index in the development of a customized decision-making tool for small-system operators and managers.

Does scale matter? A systematic review of incorporating biological realism when predicting changes in species distributions.

PubMed

Record, Sydne; Strecker, Angela; Tuanmu, Mao-Ning; Beaudrot, Lydia; Zarnetske, Phoebe; Belmaker, Jonathan; Gerstner, Beth

2018-01-01

There is ample evidence that biotic factors, such as biotic interactions and dispersal capacity, can affect species distributions and influence species' responses to climate change. However, little is known about how these factors affect predictions from species distribution models (SDMs) with respect to spatial grain and extent of the models. Understanding how spatial scale influences the effects of biological processes in SDMs is important because SDMs are one of the primary tools used by conservation biologists to assess biodiversity impacts of climate change. We systematically reviewed SDM studies published from 2003-2015 using ISI Web of Science searches to: (1) determine the current state and key knowledge gaps of SDMs that incorporate biotic interactions and dispersal; and (2) understand how choice of spatial scale may alter the influence of biological processes on SDM predictions. We used linear mixed effects models to examine how predictions from SDMs changed in response to the effects of spatial scale, dispersal, and biotic interactions. There were important biases in studies including an emphasis on terrestrial ecosystems in northern latitudes and little representation of aquatic ecosystems. Our results suggest that neither spatial extent nor grain influence projected climate-induced changes in species ranges when SDMs include dispersal or biotic interactions. We identified several knowledge gaps and suggest that SDM studies forecasting the effects of climate change should: 1) address broader ranges of taxa and locations; and 1) report the grain size, extent, and results with and without biological complexity. The spatial scale of analysis in SDMs did not affect estimates of projected range shifts with dispersal and biotic interactions. However, the lack of reporting on results with and without biological complexity precluded many studies from our analysis.

Electron energy loss spectroscopy on semiconductor heterostructures for optoelectronics and photonics applications.

PubMed

Eljarrat, A; López-Conesa, L; Estradé, S; Peiró, F

2016-05-01

In this work, we present characterization methods for the analysis of nanometer-sized devices, based on silicon and III-V nitride semiconductor materials. These methods are devised in order to take advantage of the aberration corrected scanning transmission electron microscope, equipped with a monochromator. This set-up ensures the necessary high spatial and energy resolution for the characterization of the smallest structures. As with these experiments, we aim to obtain chemical and structural information, we use electron energy loss spectroscopy (EELS). The low-loss region of EELS is exploited, which features fundamental electronic properties of semiconductor materials and facilitates a high data throughput. We show how the detailed analysis of these spectra, using theoretical models and computational tools, can enhance the analytical power of EELS. In this sense, initially, results from the model-based fit of the plasmon peak are presented. Moreover, the application of multivariate analysis algorithms to low-loss EELS is explored. Finally, some physical limitations of the technique, such as spatial delocalization, are mentioned. © 2015 The Authors Journal of Microscopy © 2015 Royal Microscopical Society.

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.

Design and application analysis of prediction system of geo-hazards based on GIS in the Three Gorges Reservoir

NASA Astrophysics Data System (ADS)

Li, Deying; Yin, Kunlong; Gao, Huaxi; Liu, Changchun

2009-10-01

Although the project of the Three Gorges Dam across the Yangtze River in China can utilize this huge potential source of hydroelectric power, and eliminate the loss of life and damage by flood, it also causes environmental problems due to the big rise and fluctuation of the water, such as geo-hazards. In order to prevent and predict geo-hazards, the establishment of prediction system of geo-hazards is very necessary. In order to implement functions of hazard prediction of regional and urban geo-hazard, single geo-hazard prediction, prediction of landslide surge and risk evaluation, logical layers of the system consist of data capturing layer, data manipulation and processing layer, analysis and application layer, and information publication layer. Due to the existence of multi-source spatial data, the research on the multi-source transformation and fusion data should be carried on in the paper. Its applicability of the system was testified on the spatial prediction of landslide hazard through spatial analysis of GIS in which information value method have been applied aims to identify susceptible areas that are possible to future landslide, on the basis of historical record of past landslide, terrain parameter, geology, rainfall and anthropogenic activity. Detailed discussion was carried out on spatial distribution characteristics of landslide hazard in the new town of Badong. These results can be used for risk evaluation. The system can be implemented as an early-warning and emergency management tool by the relevant authorities of the Three Gorges Reservoir in the future.

Bio-optical data integration based on a 4 D database system approach

NASA Astrophysics Data System (ADS)

Imai, N. N.; Shimabukuro, M. H.; Carmo, A. F. C.; Alcantara, E. H.; Rodrigues, T. W. P.; Watanabe, F. S. Y.

2015-04-01

Bio-optical characterization of water bodies requires spatio-temporal data about Inherent Optical Properties and Apparent Optical Properties which allow the comprehension of underwater light field aiming at the development of models for monitoring water quality. Measurements are taken to represent optical properties along a column of water, and then the spectral data must be related to depth. However, the spatial positions of measurement may differ since collecting instruments vary. In addition, the records should not refer to the same wavelengths. Additional difficulty is that distinct instruments store data in different formats. A data integration approach is needed to make these large and multi source data sets suitable for analysis. Thus, it becomes possible, even automatically, semi-empirical models evaluation, preceded by preliminary tasks of quality control. In this work it is presented a solution, in the stated scenario, based on spatial - geographic - database approach with the adoption of an object relational Database Management System - DBMS - due to the possibilities to represent all data collected in the field, in conjunction with data obtained by laboratory analysis and Remote Sensing images that have been taken at the time of field data collection. This data integration approach leads to a 4D representation since that its coordinate system includes 3D spatial coordinates - planimetric and depth - and the time when each data was taken. It was adopted PostgreSQL DBMS extended by PostGIS module to provide abilities to manage spatial/geospatial data. It was developed a prototype which has the mainly tools an analyst needs to prepare the data sets for analysis.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina).

PubMed

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-05-01

Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control.

Temporal Dynamics and Spatial Patterns of Aedes aegypti Breeding Sites, in the Context of a Dengue Control Program in Tartagal (Salta Province, Argentina)

PubMed Central

Espinosa, Manuel; Weinberg, Diego; Rotela, Camilo H.; Polop, Francisco; Abril, Marcelo; Scavuzzo, Carlos Marcelo

2016-01-01

Background Since 2009, Fundación Mundo Sano has implemented an Aedes aegypti Surveillance and Control Program in Tartagal city (Salta Province, Argentina). The purpose of this study was to analyze temporal dynamics of Ae. aegypti breeding sites spatial distribution, during five years of samplings, and the effect of control actions over vector population dynamics. Methodology/Principal Findings Seasonal entomological (larval) samplings were conducted in 17,815 fixed sites in Tartagal urban area between 2009 and 2014. Based on information of breeding sites abundance, from satellite remote sensing data (RS), and by the use of Geographic Information Systems (GIS), spatial analysis (hotspots and cluster analysis) and predictive model (MaxEnt) were performed. Spatial analysis showed a distribution pattern with the highest breeding densities registered in city outskirts. The model indicated that 75% of Ae. aegypti distribution is explained by 3 variables: bare soil coverage percentage (44.9%), urbanization coverage percentage(13.5%) and water distribution (11.6%). Conclusions/Significance This results have called attention to the way entomological field data and information from geospatial origin (RS/GIS) are used to infer scenarios which could then be applied in epidemiological surveillance programs and in the determination of dengue control strategies. Predictive maps development constructed with Ae. aegypti systematic spatiotemporal data, in Tartagal city, would allow public health workers to identify and target high-risk areas with appropriate and timely control measures. These tools could help decision-makers to improve health system responses and preventive measures related to vector control. PMID:27223693

Facilitating Spatial Thinking in World Geography Using Web-Based GIS

ERIC Educational Resources Information Center

Jo, Injeong; Hong, Jung Eun; Verma, Kanika

2016-01-01

Advocates for geographic information system (GIS) education contend that learning about GIS promotes students' spatial thinking. Empirical studies are still needed to elucidate the potential of GIS as an instructional tool to support spatial thinking in other geography courses. Using a non-equivalent control group research design, this study…

Teaching Mathematics for Spatial Justice: An Investigation of the Lottery

ERIC Educational Resources Information Center

Rubel, Laurie H.; Lim, Vivian Y.; Hall-Wieckert, Maren; Sullivan, Mathew

2016-01-01

This article explores integrating place-based education with critical mathematics toward teaching mathematics for spatial justice. "Local Lotto," a curricular module with associated digital tools, was designed to investigate the lottery as a critical spatial phenomenon and piloted in urban high schools. This article describes findings…

Geographic information system-based healthcare waste management planning for treatment site location and optimal transportation routeing.

PubMed

Shanmugasundaram, Jothiganesh; Soulalay, Vongdeuane; Chettiyappan, Visvanathan

2012-06-01

In Lao People's Democratic Republic (Lao PDR), a growth of healthcare centres, and the environmental hazards and public health risks typically accompanying them, increased the need for healthcare waste (HCW) management planning. An effective planning of an HCW management system including components such as the treatment plant siting and an optimized routeing system for collection and transportation of waste is deemed important. National government offices at developing countries often lack the proper tools and methodologies because of the high costs usually associated with them. However, this study attempts to demonstrate the use of an inexpensive GIS modelling tool for healthcare waste management in the country. Two areas were designed for this study on HCW management, including: (a) locating centralized treatment plants and designing optimum travel routes for waste collection from nearby healthcare facilities; and (b) utilizing existing hospital incinerators and designing optimum routes for collecting waste from nearby healthcare facilities. Spatial analysis paved the way to understand the spatial distribution of healthcare wastes and to identify hotspots of higher waste generating locations. Optimal route models were designed for collecting and transporting HCW to treatment plants, which also highlights constraints in collecting and transporting waste for treatment and disposal. The proposed model can be used as a decision support tool for the efficient management of hospital wastes by government healthcare waste management authorities and hospitals.

Spanish Transcultural Adaptation and Validity of the Behavioral Inattention Test

PubMed Central

Sánchez-Cabeza, Ángel; Huertas-Hoyas, Elisabet; Máximo-Bocanegra, Nuria; Rosa María Martínez-Piédrola; Pérez-de-Heredia-Torres, Marta

2017-01-01

Objective To adapt, validate, and translate the Behavioral Inattention Test as an assessment tool for Spanish individuals with unilateral spatial neglect. Design A cross-sectional descriptive study. Setting University laboratories. Participants A sample of 75 Spanish stroke patients and 18 healthy control subjects. Interventions Not applicable. Main Outcome Measures The Behavioral Inattention Test. Results The Spanish version of the Behavioral Inattention Test shows a high degree of reliability both in the complete test (α = .90) and in the conventional (α = .93) and behavioral subtests (α = .75). The concurrent validity between the total conventional and behavioral scores was high (r = −.80; p < 0.001). Significant differences were found between patients with and without unilateral spatial neglect (p < 0.001). In the comparison between right and left damaged sides, differences were found in all items, except for article reading (p = 0.156) and card sorting (p = 0.117). Conclusions This measure is a useful tool for evaluating unilateral spatial neglect as it provides information on everyday problems. The BIT discriminates between stroke patients with and without unilateral spatial neglect. This measure constitutes a reliable tool for the diagnosis, planning, performance, and design of specific treatment programs intended to improve the functionality and quality of life of people with unilateral spatial neglect. PMID:29097959

EVALUATING HYDROLOGICAL RESPONSE TO ...

EPA Pesticide Factsheets

Studies of future management and policy options based on different assumptions provide a mechanism to examine possible outcomes and especially their likely benefits or consequences. Planning and assessment in land and water resource management are evolving toward complex, spatially explicit regional assessments. These problems have to be addressed with distributed models that can compute runoff and erosion at different spatial and temporal scales. The extensive data requirements and the difficult task of building input parameter files, however, have long been an obstacle to the timely and cost-effective use of such complex models by resource managers. The U.S. EPA Landscape Ecology Branch in collaboration with the USDA-ARS Southwest Watershed Research Center has developed a geographic information system (GIS) tool to facilitate this process. A GIS provides the framework within which spatially distributed data are collected and used to prepare model input files, and model results are evaluated. The Automated Geospatial Watershed Assessment (AGWA) tool uses widely available standardized spatial datasets that can be obtained via the internet at no cost to the user. The data are used to develop input parameter files for KINEROS2 and SWAT, two watershed runoff and erosion simulation models that operate at different spatial and temporal scales. AGWA automates the process of transforming digital data into simulation model results and provides a visualization tool

Localized Overheating Phenomena and Optimization of Spark-Plasma Sintering Tooling Design

PubMed Central

Giuntini, Diletta; Olevsky, Eugene A.; Garcia-Cardona, Cristina; Maximenko, Andrey L.; Yurlova, Maria S.; Haines, Christopher D.; Martin, Darold G.; Kapoor, Deepak

2013-01-01

The present paper shows the application of a three-dimensional coupled electrical, thermal, mechanical finite element macro-scale modeling framework of Spark Plasma Sintering (SPS) to an actual problem of SPS tooling overheating, encountered during SPS experimentation. The overheating phenomenon is analyzed by varying the geometry of the tooling that exhibits the problem, namely by modeling various tooling configurations involving sequences of disk-shape spacers with step-wise increasing radii. The analysis is conducted by means of finite element simulations, intended to obtain temperature spatial distributions in the graphite press-forms, including punches, dies, and spacers; to identify the temperature peaks and their respective timing, and to propose a more suitable SPS tooling configuration with the avoidance of the overheating as a final aim. Electric currents-based Joule heating, heat transfer, mechanical conditions, and densification are imbedded in the model, utilizing the finite-element software COMSOL™, which possesses a distinguishing ability of coupling multiple physics. Thereby the implementation of a finite element method applicable to a broad range of SPS procedures is carried out, together with the more specific optimization of the SPS tooling design when dealing with excessive heating phenomena. PMID:28811398

Marine spatial planning in practice

NASA Astrophysics Data System (ADS)

Collie, Jeremy S.; (Vic) Adamowicz, W. L.; Beck, Michael W.; Craig, Bethany; Essington, Timothy E.; Fluharty, David; Rice, Jake; Sanchirico, James N.

2013-01-01

Multiple competing uses of continental-shelf environments have led to a proliferation of marine spatial planning initiatives, together with expert guidance on marine spatial planning. This study provides an empirical review of marine spatial plans, their attributes, and the extent to which the expert guidance is actually being followed. We performed a structured review of 16 existing marine spatial plans and created an idealized marine spatial plan from the steps included in recent expert papers. A cluster analysis of the yes/no answers to 28 questions was used to ordinate the 16 marine spatial plans and to compare them with the idealized plan. All the plans that have been implemented have a high-level government mandate and the authority to implement spatial planning vested in existing institutions. Almost all the plans used data with clear criteria for data inclusion. Stakeholders were included in almost all the plans; they did not participate in all stages of the planning process but their roles were generally clearly defined. Decision-support tools were applied inconsistently across plans and were seldom used dynamically over time. Most spatial planning processes did not select specific outcomes, such as preferred use scenarios. Success is defined inconsistently across plans; in half the cases there are no metrics of success with reference benchmarks. Although monitoring is included in the majority of plans, only in some cases do monitoring results feed back into management decisions. The process of marine spatial planning had advanced in that some of the more recent plans were developed more quickly and contain more desirable attributes than earlier plans. Even so, existing marine spatial plans are heterogeneous—there are essential ingredients, but no single recipe for success.

RIMS: An Integrated Mapping and Analysis System with Applications to Earth Sciences and Hydrology

NASA Astrophysics Data System (ADS)

Proussevitch, A. A.; Glidden, S.; Shiklomanov, A. I.; Lammers, R. B.

2011-12-01

A web-based information and computational system for analysis of spatially distributed Earth system, climate, and hydrologic data have been developed. The System allows visualization, data exploration, querying, manipulation and arbitrary calculations with any loaded gridded or vector polygon dataset. The system's acronym, RIMS, stands for its core functionality as a Rapid Integrated Mapping System. The system can be deployed for a Global scale projects as well as for regional hydrology and climatology studies. In particular, the Water Systems Analysis Group of the University of New Hampshire developed the global and regional (Northern Eurasia, pan-Arctic) versions of the system with different map projections and specific data. The system has demonstrated its potential for applications in other fields of Earth sciences and education. The key Web server/client components of the framework include (a) a visualization engine built on Open Source libraries (GDAL, PROJ.4, etc.) that are utilized in a MapServer; (b) multi-level data querying tools built on XML server-client communication protocols that allow downloading map data on-the-fly to a client web browser; and (c) data manipulation and grid cell level calculation tools that mimic desktop GIS software functionality via a web interface. Server side data management of the system is designed around a simple database of dataset metadata facilitating mounting of new data to the system and maintaining existing data in an easy manner. RIMS contains "built-in" river network data that allows for query of upstream areas on-demand which can be used for spatial data aggregation and analysis of sub-basin areas. RIMS is an ongoing effort and currently being used to serve a number of websites hosting a suite of hydrologic, environmental and other GIS data.

Cost analysis of the development and implementation of a spatial decision support system for malaria elimination in Solomon Islands.

PubMed

Marston, Luke; Kelly, Gerard C; Hale, Erick; Clements, Archie C A; Hodge, Andrew; Jimenez-Soto, Eliana

2014-08-18

The goal of malaria elimination faces numerous challenges. New tools are required to support the scale up of interventions and improve national malaria programme capacity to conduct detailed surveillance. This study investigates the cost factors influencing the development and implementation of a spatial decision support system (SDSS) for malaria elimination in the two elimination provinces of Isabel and Temotu, Solomon Islands. Financial and economic costs to develop and implement a SDSS were estimated using the Solomon Islands programme's financial records. Using an ingredients approach, verified by stakeholders and operational reports, total costs for each province were quantified. A budget impact sensitivity analysis was conducted to investigate the influence of variations in standard budgetary components on the costs and to identify potential cost savings. A total investment of US$ 96,046 (2012 constant dollars) was required to develop and implement the SDSS in two provinces (Temotu Province US$ 49,806 and Isabel Province US$ 46,240). The single largest expense category was for computerized equipment totalling approximately US$ 30,085. Geographical reconnaissance was the most expensive phase of development and implementation, accounting for approximately 62% of total costs. Sensitivity analysis identified different cost factors between the provinces. Reduced equipment costs would deliver a budget saving of approximately 10% in Isabel Province. Combined travel costs represented the greatest influence on the total budget in the more remote Temotu Province. This study provides the first cost analysis of an operational surveillance tool used specifically for malaria elimination in the South-West Pacific. It is demonstrated that the costs of such a decision support system are driven by specialized equipment and travel expenses. Such factors should be closely scrutinized in future programme budgets to ensure maximum efficiencies are gained and available resources are allocated effectively.

Energetically optimal travel across terrain: visualizations and a new metric of geographic distance with anthropological applications

NASA Astrophysics Data System (ADS)

Wood, Brian M.; Wood, Zoë J.

2006-01-01

We present a visualization and computation tool for modeling the caloric cost of pedestrian travel across three dimensional terrains. This tool is being used in ongoing archaeological research that analyzes how costs of locomotion affect the spatial distribution of trails and artifacts across archaeological landscapes. Throughout human history, traveling by foot has been the most common form of transportation, and therefore analyses of pedestrian travel costs are important for understanding prehistoric patterns of resource acquisition, migration, trade, and political interaction. Traditionally, archaeologists have measured geographic proximity based on "as the crow flies" distance. We propose new methods for terrain visualization and analysis based on measuring paths of least caloric expense, calculated using well established metabolic equations. Our approach provides a human centered metric of geographic closeness, and overcomes significant limitations of available Geographic Information System (GIS) software. We demonstrate such path computations and visualizations applied to archaeological research questions. Our system includes tools to visualize: energetic cost surfaces, comparisons of the elevation profiles of shortest paths versus least cost paths, and the display of paths of least caloric effort on Digital Elevation Models (DEMs). These analysis tools can be applied to calculate and visualize 1) likely locations of prehistoric trails and 2) expected ratios of raw material types to be recovered at archaeological sites.

Matching spatial with ontological brain regions using Java tools for visualization, database access, and integrated data analysis.

PubMed

Bezgin, Gleb; Reid, Andrew T; Schubert, Dirk; Kötter, Rolf

2009-01-01

Brain atlases are widely used in experimental neuroscience as tools for locating and targeting specific brain structures. Delineated structures in a given atlas, however, are often difficult to interpret and to interface with database systems that supply additional information using hierarchically organized vocabularies (ontologies). Here we discuss the concept of volume-to-ontology mapping in the context of macroscopical brain structures. We present Java tools with which we have implemented this concept for retrieval of mapping and connectivity data on the macaque brain from the CoCoMac database in connection with an electronic version of "The Rhesus Monkey Brain in Stereotaxic Coordinates" authored by George Paxinos and colleagues. The software, including our manually drawn monkey brain template, can be downloaded freely under the GNU General Public License. It adds value to the printed atlas and has a wider (neuro-)informatics application since it can read appropriately annotated data from delineated sections of other species and organs, and turn them into 3D registered stacks. The tools provide additional features, including visualization and analysis of connectivity data, volume and centre-of-mass estimates, and graphical manipulation of entire structures, which are potentially useful for a range of research and teaching applications.

A geomatic methodology for spatio-temporal analysis of climatologic variables and water related diseases

NASA Astrophysics Data System (ADS)

Quentin, E.; Gómez Albores, M. A.; Díaz Delgado, C.

2009-04-01

The main objective of this research is to propose, by the way of geomatic developments, an integrated tool to analyze and model the spatio-temporal pattern of human diseases related to environmental conditions, in particular the ones that are linked to water resources. The geomatic developments follows four generic steps : requirement analysis, conceptual modeling, geomatic modeling and implementation (in Idrisi GIS software). A first development consists of the preprocessing of water, population and health data in order to facilitate the conversion and validation of tabular data into the required structure for spatio-temporal analysis. Three parallel developments follow : water balance, demographic state and evolution, epidemiological measures (morbidity and mortality rates, diseases burden). The new geomatic modules in their actual state have been tested on various regions of Mexico Republic (Lerma watershed, Chiapas state) focusing on diarrhea and vector borne diseases (dengue and malaria) and considering records over the last decade : a yearly as well as seasonal spreading trend can be observed in correlation with precipitation and temperature data. In an ecohealth perspective, the geomatic approach results particularly appropriate since one of its purposes is the integration of the various spatial themes implied in the study problem, environmental as anthropogenic. By the use of powerful spatial analysis functions, it permits the detection of spatial trends which, combined to the temporal evolution, can be of particularly use for example in climate change context, if sufficiently valid historical data can be obtain.

Mobile Visualization and Analysis Tools for Spatial Time-Series Data

NASA Astrophysics Data System (ADS)

Eberle, J.; Hüttich, C.; Schmullius, C.

2013-12-01

The Siberian Earth System Science Cluster (SIB-ESS-C) provides access and analysis services for spatial time-series data build on products from the Moderate Resolution Imaging Spectroradiometer (MODIS) and climate data from meteorological stations. Until now a webportal for data access, visualization and analysis with standard-compliant web services was developed for SIB-ESS-C. As a further enhancement a mobile app was developed to provide an easy access to these time-series data for field campaigns. The app sends the current position from the GPS receiver and a specific dataset (like land surface temperature or vegetation indices) - selected by the user - to our SIB-ESS-C web service and gets the requested time-series data for the identified pixel back in real-time. The data is then being plotted directly in the app. Furthermore the user has possibilities to analyze the time-series data for breaking points and other phenological values. These processings are executed on demand of the user on our SIB-ESS-C web server and results are transfered to the app. Any processing can also be done at the SIB-ESS-C webportal. The aim of this work is to make spatial time-series data and analysis functions available for end users without the need of data processing. In this presentation the author gives an overview on this new mobile app, the functionalities, the technical infrastructure as well as technological issues (how the app was developed, our made experiences).

Spatio-Temporal Trends and Risk Factors for Shigella from 2001 to 2011 in Jiangsu Province, People's Republic of China

PubMed Central

Bao, Changjun; Hu, Jianli; Liu, Wendong; Liang, Qi; Wu, Ying; Norris, Jessie; Peng, Zhihang; Yu, Rongbin; Shen, Hongbing; Chen, Feng

2014-01-01

Objective This study aimed to describe the spatial and temporal trends of Shigella incidence rates in Jiangsu Province, People's Republic of China. It also intended to explore complex risk modes facilitating Shigella transmission. Methods County-level incidence rates were obtained for analysis using geographic information system (GIS) tools. Trend surface and incidence maps were established to describe geographic distributions. Spatio-temporal cluster analysis and autocorrelation analysis were used for detecting clusters. Based on the number of monthly Shigella cases, an autoregressive integrated moving average (ARIMA) model successfully established a time series model. A spatial correlation analysis and a case-control study were conducted to identify risk factors contributing to Shigella transmissions. Results The far southwestern and northwestern areas of Jiangsu were the most infected. A cluster was detected in southwestern Jiangsu (LLR = 11674.74, P<0.001). The time series model was established as ARIMA (1, 12, 0), which predicted well for cases from August to December, 2011. Highways and water sources potentially caused spatial variation in Shigella development in Jiangsu. The case-control study confirmed not washing hands before dinner (OR = 3.64) and not having access to a safe water source (OR = 2.04) as the main causes of Shigella in Jiangsu Province. Conclusion Improvement of sanitation and hygiene should be strengthened in economically developed counties, while access to a safe water supply in impoverished areas should be increased at the same time. PMID:24416167

PlanetServer: Innovative approaches for the online analysis of hyperspectral satellite data from Mars

NASA Astrophysics Data System (ADS)

Oosthoek, J. H. P.; Flahaut, J.; Rossi, A. P.; Baumann, P.; Misev, D.; Campalani, P.; Unnithan, V.

2014-06-01

PlanetServer is a WebGIS system, currently under development, enabling the online analysis of Compact Reconnaissance Imaging Spectrometer (CRISM) hyperspectral data from Mars. It is part of the EarthServer project which builds infrastructure for online access and analysis of huge Earth Science datasets. Core functionality consists of the rasdaman Array Database Management System (DBMS) for storage, and the Open Geospatial Consortium (OGC) Web Coverage Processing Service (WCPS) for data querying. Various WCPS queries have been designed to access spatial and spectral subsets of the CRISM data. The client WebGIS, consisting mainly of the OpenLayers javascript library, uses these queries to enable online spatial and spectral analysis. Currently the PlanetServer demonstration consists of two CRISM Full Resolution Target (FRT) observations, surrounding the NASA Curiosity rover landing site. A detailed analysis of one of these observations is performed in the Case Study section. The current PlanetServer functionality is described step by step, and is tested by focusing on detecting mineralogical evidence described in earlier Gale crater studies. Both the PlanetServer methodology and its possible use for mineralogical studies will be further discussed. Future work includes batch ingestion of CRISM data and further development of the WebGIS and analysis tools.

Local indicators of geocoding accuracy (LIGA): theory and application

PubMed Central

Jacquez, Geoffrey M; Rommel, Robert

2009-01-01

Background Although sources of positional error in geographic locations (e.g. geocoding error) used for describing and modeling spatial patterns are widely acknowledged, research on how such error impacts the statistical results has been limited. In this paper we explore techniques for quantifying the perturbability of spatial weights to different specifications of positional error. Results We find that a family of curves describes the relationship between perturbability and positional error, and use these curves to evaluate sensitivity of alternative spatial weight specifications to positional error both globally (when all locations are considered simultaneously) and locally (to identify those locations that would benefit most from increased geocoding accuracy). We evaluate the approach in simulation studies, and demonstrate it using a case-control study of bladder cancer in south-eastern Michigan. Conclusion Three results are significant. First, the shape of the probability distributions of positional error (e.g. circular, elliptical, cross) has little impact on the perturbability of spatial weights, which instead depends on the mean positional error. Second, our methodology allows researchers to evaluate the sensitivity of spatial statistics to positional accuracy for specific geographies. This has substantial practical implications since it makes possible routine sensitivity analysis of spatial statistics to positional error arising in geocoded street addresses, global positioning systems, LIDAR and other geographic data. Third, those locations with high perturbability (most sensitive to positional error) and high leverage (that contribute the most to the spatial weight being considered) will benefit the most from increased positional accuracy. These are rapidly identified using a new visualization tool we call the LIGA scatterplot. Herein lies a paradox for spatial analysis: For a given level of positional error increasing sample density to more accurately follow the underlying population distribution increases perturbability and introduces error into the spatial weights matrix. In some studies positional error may not impact the statistical results, and in others it might invalidate the results. We therefore must understand the relationships between positional accuracy and the perturbability of the spatial weights in order to have confidence in a study's results. PMID:19863795

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.

Solutions Network Formulation Report. NASA's Potential Contributions using ASTER Data in Marine Hazard Mitigation

NASA Technical Reports Server (NTRS)

Fletcher, Rose

2010-01-01

The 28-foot storm surge from Hurricane Katrina pushed inland along bays and rivers for a distance of 12 miles in some areas, contributing to the damage or destruction of about half of the fleet of boats in coastal Mississippi. Most of those boats had sought refuge in back bays and along rivers. Some boats were spared damage because the owners chose their mooring site well. Gulf mariners need a spatial analysis tool that provides guidance on the safest places to anchor their boats during future hurricanes. This product would support NOAA s mission to minimize the effects of coastal hazards through awareness, education, and mitigation strategies and could be incorporated in the Coastal Risk Atlas decision support tool.

New Techniques for the Generation and Analysis of Tailored Microbial Systems on Surfaces.

PubMed

Furst, Ariel L; Smith, Matthew J; Francis, Matthew B

2018-05-17

The interactions between microbes and surfaces provide critically important cues that control the behavior and growth of the cells. As our understanding of complex microbial communities improves, there is a growing need for experimental tools that can establish and control the spatial arrangements of these cells in a range of contexts. Recent improvements in methods to attach bacteria and yeast to nonbiological substrates, combined with an expanding set of techniques available to study these cells, position this field for many new discoveries. Improving methods for controlling the immobilization of bacteria provides powerful experimental tools for testing hypotheses regarding microbiome interactions, studying the transfer of nutrients between bacterial species, and developing microbial communities for green energy production and pollution remediation.

High Resolution Mesoscale Weather Data Improvement to Spatial Effects for Dose-Rate Contour Plot Predictions

DTIC Science & Technology

2007-03-01

time. This is a very powerful tool in determining fine spatial resolution , as boundary conditions are not only updated at every timestep, but the ...HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT PREDICTIONS THESIS Christopher P...11 1 HIGH RESOLUTION MESOSCALE WEATHER DATA IMPROVEMENT TO SPATIAL EFFECTS FOR DOSE-RATE CONTOUR PLOT

Exploratory spatial analysis of pilot fatality rates in general aviation crashes using geographic information systems.

PubMed

Grabowski, Jurek G; Curriero, Frank C; Baker, Susan P; Li, Guohua

2002-03-01

Geographic information systems and exploratory spatial analysis were used to describe the geographic characteristics of pilot fatality rates in 1983-1998 general aviation crashes within the continental United States. The authors plotted crash sites on a digital map; rates were computed at regular grid intersections and then interpolated by using geographic information systems. A test for significance was performed by using Monte Carlo simulations. Further analysis compared low-, medium-, and high-rate areas in relation to pilot characteristics, aircraft type, and crash circumstance. Of the 14,051 general aviation crashes studied, 31% were fatal. Seventy-four geographic areas were categorized as having low fatality rates and 53 as having high fatality rates. High-fatality-rate areas tended to be mountainous, such as the Rocky Mountains and the Appalachian region, whereas low-rate areas were relatively flat, such as the Great Plains. Further analysis comparing low-, medium-, and high-fatality-rate areas revealed that crashes in high-fatality-rate areas were more likely than crashes in other areas to have occurred under instrument meteorologic conditions and to involve aircraft fire. This study demonstrates that geographic information systems are a valuable tool for injury prevention and aviation safety research.

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

PubMed

Suo, Anning; Wang, Chen; Zhang, Minghui

2016-01-01

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

Spatiotemporal Thinking in the Geosciences

NASA Astrophysics Data System (ADS)

Shipley, T. F.; Manduca, C. A.; Ormand, C. J.; Tikoff, B.

2011-12-01

Reasoning about spatial relations is a critical skill for geoscientists. Within the geosciences different disciplines may reason about different sorts of relationships. These relationships may span vastly different spatial and temporal scales (from the spatial alignment in atoms in crystals to the changes in the shape of plates). As part of work in a research center on spatial thinking in STEM education, we have been working to classify the spatial skills required in geology, develop tests for each spatial skill, and develop the cognitive science tools to promote the critical spatial reasoning skills. Research in psychology, neurology and linguistics supports a broad classification of spatial skills along two dimensions: one versus many objects (which roughly translates to object- focused and navigation focused skills) and static versus dynamic spatial relations. The talk will focus on the interaction of space and time in spatial cognition in the geosciences. We are working to develop measures of skill in visualizing spatiotemporal changes. A new test developed to measure visualization of brittle deformations will be presented. This is a skill that has not been clearly recognized in the cognitive science research domain and thus illustrates the value of interdisciplinary work that combines geosciences with cognitive sciences. Teaching spatiotemporal concepts can be challenging. Recent theoretical work suggests analogical reasoning can be a powerful tool to aid student learning to reason about temporal relations using spatial skills. Recent work in our lab has found that progressive alignment of spatial and temporal scales promotes accurate reasoning about temporal relations at geological time scales.

Public health, GIS, and the internet.

PubMed

Croner, Charles M

2003-01-01

Internet access and use of georeferenced public health information for GIS application will be an important and exciting development for the nation's Department of Health and Human Services and other health agencies in this new millennium. Technological progress toward public health geospatial data integration, analysis, and visualization of space-time events using the Web portends eventual robust use of GIS by public health and other sectors of the economy. Increasing Web resources from distributed spatial data portals and global geospatial libraries, and a growing suite of Web integration tools, will provide new opportunities to advance disease surveillance, control, and prevention, and insure public access and community empowerment in public health decision making. Emerging supercomputing, data mining, compression, and transmission technologies will play increasingly critical roles in national emergency, catastrophic planning and response, and risk management. Web-enabled public health GIS will be guided by Federal Geographic Data Committee spatial metadata, OpenGIS Web interoperability, and GML/XML geospatial Web content standards. Public health will become a responsive and integral part of the National Spatial Data Infrastructure.

Near-Infrared Spatially Resolved Spectroscopy for Tablet Quality Determination.

PubMed

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

2015-12-01

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

Spatial Allocator for air quality modeling

EPA Pesticide Factsheets

The Spatial Allocator is a set of tools that helps users manipulate and generate data files related to emissions and air quality modeling without requiring the use of a commercial Geographic Information System.

Development of a prototype spatial information processing system for hydrologic research

NASA Technical Reports Server (NTRS)

Sircar, Jayanta K.

1991-01-01

Significant advances have been made in the last decade in the areas of Geographic Information Systems (GIS) and spatial analysis technology, both in hardware and software. Science user requirements are so problem specific that currently no single system can satisfy all of the needs. The work presented here forms part of a conceptual framework for an all-encompassing science-user workstation system. While definition and development of the system as a whole will take several years, it is intended that small scale projects such as the current work will address some of the more short term needs. Such projects can provide a quick mechanism to integrate tools into the workstation environment forming a larger, more complete hydrologic analysis platform. Described here are two components that are very important to the practical use of remote sensing and digital map data in hydrology. Described here is a graph-theoretic technique to rasterize elevation contour maps. Also described is a system to manipulate synthetic aperture radar (SAR) data files and extract soil moisture data.

Digital Hadron Calorimetry

NASA Astrophysics Data System (ADS)

Bilki, Burak

2018-03-01

The Particle Flow Algorithms attempt to measure each particle in a hadronic jet individually, using the detector providing the best energy/momentum resolution. Therefore, the spatial segmentation of the calorimeter plays a crucial role. In this context, the CALICE Collaboration developed the Digital Hadron Calorimeter. The Digital Hadron Calorimeter uses Resistive Plate Chambers as active media and has a 1-bit resolution (digital) readout of 1 × 1 cm2 pads. The calorimeter was tested with steel and tungsten absorber structures, as well as with no absorber structure, at the Fermilab and CERN test beam facilities over several years. In addition to conventional calorimetric measurements, the Digital Hadron Calorimeter offers detailed measurements of event shapes, rigorous tests of simulation models and various tools for improved performance due to its very high spatial granularity. Here we report on the results from the analysis of pion and positron events. Results of comparisons with the Monte Carlo simulations are also discussed. The analysis demonstrates the unique utilization of detailed event topologies.

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.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders.

PubMed

Tapia-McClung, Horacio; Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology.

Development of a 3D GIS and its application to karst areas

NASA Astrophysics Data System (ADS)

Wu, Qiang; Xu, Hua; Zhou, Wanfang

2008-05-01

There is a growing interest in modeling and analyzing karst phenomena in three dimensions. This paper integrates geology, groundwater hydrology, geographic information system (GIS), database management system (DBMS), visualization and data mining to study karst features in Huaibei, China. The 3D geo-objects retrieved from the karst area are analyzed and mapped into different abstract levels. The spatial relationships among the objects are constructed by a dual-linker. The shapes of the 3D objects and the topological models with attributes are stored and maintained in the DBMS. Spatial analysis was then used to integrate the data in the DBMS and the 3D model to form a virtual reality (VR) to provide analytical functions such as distribution analysis, correlation query, and probability assessment. The research successfully implements 3D modeling and analyses in the karst area, and meanwhile provides an efficient tool for government policy-makers to set out restrictions on water resource development in the area.

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.

Quantifying Human Visible Color Variation from High Definition Digital Images of Orb Web Spiders

PubMed Central

Ajuria Ibarra, Helena; Rao, Dinesh

2016-01-01

Digital processing and analysis of high resolution images of 30 individuals of the orb web spider Verrucosa arenata were performed to extract and quantify human visible colors present on the dorsal abdomen of this species. Color extraction was performed with minimal user intervention using an unsupervised algorithm to determine groups of colors on each individual spider, which was then analyzed in order to quantify and classify the colors obtained, both spatially and using energy and entropy measures of the digital images. Analysis shows that the colors cover a small region of the visible spectrum, are not spatially homogeneously distributed over the patterns and from an entropic point of view, colors that cover a smaller region on the whole pattern carry more information than colors covering a larger region. This study demonstrates the use of processing tools to create automatic systems to extract valuable information from digital images that are precise, efficient and helpful for the understanding of the underlying biology. PMID:27902724

Automated Ontology Generation Using Spatial Reasoning

NASA Astrophysics Data System (ADS)

Coalter, Alton; Leopold, Jennifer L.

Recently there has been much interest in using ontologies to facilitate knowledge representation, integration, and reasoning. Correspondingly, the extent of the information embodied by an ontology is increasing beyond the conventional is_a and part_of relationships. To address these requirements, a vast amount of digitally available information may need to be considered when building ontologies, prompting a desire for software tools to automate at least part of the process. The main efforts in this direction have involved textual information retrieval and extraction methods. For some domains extension of the basic relationships could be enhanced further by the analysis of 2D and/or 3D images. For this type of media, image processing algorithms are more appropriate than textual analysis methods. Herein we present an algorithm that, given a collection of 3D image files, utilizes Qualitative Spatial Reasoning (QSR) to automate the creation of an ontology for the objects represented by the images, relating the objects in terms of is_a and part_of relationships and also through unambiguous Relational Connection Calculus (RCC) relations.

Examining Chemistry Students Visual-Perceptual Skills Using the VSCS tool and Interview Data

NASA Astrophysics Data System (ADS)

Christian, Caroline

The Visual-Spatial Chemistry Specific (VSCS) assessment tool was developed to test students' visual-perceptual skills, which are required to form a mental image of an object. The VSCS was designed around the theoretical framework of Rochford and Archer that provides eight distinct and well-defined visual-perceptual skills with identified problems students might have with each skill set. Factor analysis was used to analyze the results during the validation process of the VSCS. Results showed that the eight factors could not be separated from each other, but instead two factors emerged as significant to the data. These two factors have been defined and described as a general visual-perceptual skill (factor 1) and a skill that adds on a second level of complexity by involving multiple viewpoints such as changing frames of reference. The questions included in the factor analysis were bolstered by the addition of an item response theory (IRT) analysis. Interviews were also conducted with twenty novice students to test face validity of the tool, and to document student approaches at solving visualization problems of this type. Students used five main physical resources or processes to solve the questions, but the resource that was the most successful was handling or building a physical representation of an object.

Remote sensing and GIS integration: Towards intelligent imagery within a spatial data infrastructure

NASA Astrophysics Data System (ADS)

Abdelrahim, Mohamed Mahmoud Hosny

2001-11-01

In this research, an "Intelligent Imagery System Prototype" (IISP) was developed. IISP is an integration tool that facilitates the environment for active, direct, and on-the-fly usage of high resolution imagery, internally linked to hidden GIS vector layers, to query the real world phenomena and, consequently, to perform exploratory types of spatial analysis based on a clear/undisturbed image scene. The IISP was designed and implemented using the software components approach to verify the hypothesis that a fully rectified, partially rectified, or even unrectified digital image can be internally linked to a variety of different hidden vector databases/layers covering the end user area of interest, and consequently may be reliably used directly as a base for "on-the-fly" querying of real-world phenomena and for performing exploratory types of spatial analysis. Within IISP, differentially rectified, partially rectified (namely, IKONOS GEOCARTERRA(TM)), and unrectified imagery (namely, scanned aerial photographs and captured video frames) were investigated. The system was designed to handle four types of spatial functions, namely, pointing query, polygon/line-based image query, database query, and buffering. The system was developed using ESRI MapObjects 2.0a as the core spatial component within Visual Basic 6.0. When used to perform the pre-defined spatial queries using different combinations of image and vector data, the IISP provided the same results as those obtained by querying pre-processed vector layers even when the image used was not orthorectified and the vector layers had different parameters. In addition, the real-time pixel location orthorectification technique developed and presented within the IKONOS GEOCARTERRA(TM) case provided a horizontal accuracy (RMSE) of +/- 2.75 metres. This accuracy is very close to the accuracy level obtained when purchasing the orthorectified IKONOS PRECISION products (RMSE of +/- 1.9 metre). The latter cost approximately four times as much as the IKONOS GEOCARTERRA(TM) products. The developed IISP is a step closer towards the direct and active involvement of high-resolution remote sensing imagery in querying the real world and performing exploratory types of spatial analysis. (Abstract shortened by UMI.)

Understanding Stellar Light Spatial Inhomogeneities and Time Variability

NASA Technical Reports Server (NTRS)

Uitenbroek, Han; Sasselov, Dimitar D.

2000-01-01

We would like the opportunity to thank NASA for supporting our efforts to construct tools to analyze the spectra of spatially inhomogeneous and temporally varying stellar atmospheres. This financial support has allowed us to a versatile radiative transfer code that can be used for many different applications. With this numerical code we have written a point-and-click analysis package written in IDL that can be used to look extensively at the generated output data. Below we describe the most recent results obtained with our transfer code and list papers that have appeared with these results. Although we have not been able to produce as many time-dependent calculations as we had hoped (mainly because of programmatic reasons; Sasselov took another position halfway through the grant), we believe we have

Spectral-spatial classification using tensor modeling for cancer detection with hyperspectral imaging

NASA Astrophysics Data System (ADS)

Lu, Guolan; Halig, Luma; Wang, Dongsheng; Chen, Zhuo Georgia; Fei, Baowei

2014-03-01

As an emerging technology, hyperspectral imaging (HSI) combines both the chemical specificity of spectroscopy and the spatial resolution of imaging, which may provide a non-invasive tool for cancer detection and diagnosis. Early detection of malignant lesions could improve both survival and quality of life of cancer patients. In this paper, we introduce a tensor-based computation and modeling framework for the analysis of hyperspectral images to detect head and neck cancer. The proposed classification method can distinguish between malignant tissue and healthy tissue with an average sensitivity of 96.97% and an average specificity of 91.42% in tumor-bearing mice. The hyperspectral imaging and classification technology has been demonstrated in animal models and can have many potential applications in cancer research and management.

Active Optics: stress polishing of toric mirrors for the VLT SPHERE adaptive optics system.

PubMed

Hugot, Emmanuel; Ferrari, Marc; El Hadi, Kacem; Vola, Pascal; Gimenez, Jean Luc; Lemaitre, Gérard R; Rabou, Patrick; Dohlen, Kjetil; Puget, Pascal; Beuzit, Jean Luc; Hubin, Norbert

2009-05-20

The manufacturing of toric mirrors for the Very Large Telescope-Spectro-Polarimetric High-Contrast Exoplanet Research instrument (SPHERE) is based on Active Optics and stress polishing. This figuring technique allows minimizing mid and high spatial frequency errors on an aspherical surface by using spherical polishing with full size tools. In order to reach the tight precision required, the manufacturing error budget is described to optimize each parameter. Analytical calculations based on elasticity theory and finite element analysis lead to the mechanical design of the Zerodur blank to be warped during the stress polishing phase. Results on the larger (366 mm diameter) toric mirror are evaluated by interferometry. We obtain, as expected, a toric surface within specification at low, middle, and high spatial frequencies ranges.

WormGUIDES: an interactive single cell developmental atlas and tool for collaborative multidimensional data exploration.

PubMed

Santella, Anthony; Catena, Raúl; Kovacevic, Ismar; Shah, Pavak; Yu, Zidong; Marquina-Solis, Javier; Kumar, Abhishek; Wu, Yicong; Schaff, James; Colón-Ramos, Daniel; Shroff, Hari; Mohler, William A; Bao, Zhirong

2015-06-09

Imaging and image analysis advances are yielding increasingly complete and complicated records of cellular events in tissues and whole embryos. The ability to follow hundreds to thousands of cells at the individual level demands a spatio-temporal data infrastructure: tools to assemble and collate knowledge about development spatially in a manner analogous to geographic information systems (GIS). Just as GIS indexes items or events based on their spatio-temporal or 4D location on the Earth these tools would organize knowledge based on location within the tissues or embryos. Developmental processes are highly context-specific, but the complexity of the 4D environment in which they unfold is a barrier to assembling an understanding of any particular process from diverse sources of information. In the same way that GIS aids the understanding and use of geo-located large data sets, software can, with a proper frame of reference, allow large biological data sets to be understood spatially. Intuitive tools are needed to navigate the spatial structure of complex tissue, collate large data sets and existing knowledge with this spatial structure and help users derive hypotheses about developmental mechanisms. Toward this goal we have developed WormGUIDES, a mobile application that presents a 4D developmental atlas for Caenorhabditis elegans. The WormGUIDES mobile app enables users to navigate a 3D model depicting the nuclear positions of all cells in the developing embryo. The identity of each cell can be queried with a tap, and community databases searched for available information about that cell. Information about ancestry, fate and gene expression can be used to label cells and craft customized visualizations that highlight cells as potential players in an event of interest. Scenes are easily saved, shared and published to other WormGUIDES users. The mobile app is available for Android and iOS platforms. WormGUIDES provides an important tool for examining developmental processes and developing mechanistic hypotheses about their control. Critically, it provides the typical end user with an intuitive interface for developing and sharing custom visualizations of developmental processes. Equally important, because users can select cells based on their position and search for information about them, the app also serves as a spatially organized index into the large body of knowledge available to the C. elegans community online. Moreover, the app can be used to create and publish the result of exploration: interactive content that brings other researchers and students directly to the spatio-temporal point of insight. Ultimately the app will incorporate a detailed time lapse record of cell shape, beginning with neurons. This will add the key ability to navigate and understand the developmental events that result in the coordinated and precise emergence of anatomy, particularly the wiring of the nervous system.

PAD-US: National Inventory of Protected Areas

USGS Publications Warehouse

Gergely, Kevin J.; McKerrow, Alexa

2013-11-12

The Gap Analysis Program produces data and tools that help meet critical national challenges such as biodiversity conservation, renewable energy development, climate change adaptation, and infrastructure investment. The Protected Areas Database of the United States (PAD-US) is the official inventory of protected open space in the United States. With over 715 million acres in thousands of holdings, the spatial data in PAD-US include public lands held in trust by national, State, and some local governments, and by some nonprofit conservation organizations.

Hailstorm forecast from stability indexes in Southwestern France

NASA Astrophysics Data System (ADS)

Melcón, Pablo; Merino, Andrés; Sánchez, José Luis; Dessens, Jean; Gascón, Estíbaliz; Berthet, Claude; López, Laura; García-Ortega, Eduardo

2016-04-01

Forecasting hailstorms is a difficult task because of their small spatial and temporal scales. Over recent decades, stability indexes have been commonly used in operational forecasting to provide a simplified representation of different thermodynamic characteristics of the atmosphere, regarding the onset of convective events. However, they are estimated from vertical profiles obtained by radiosondes, which are usually available only twice a day and have limited spatial representativeness. Numerical models predictions can be used to overcome these drawbacks, providing vertical profiles with higher spatiotemporal resolution. The main objective of this study is to create a tool for hail prediction in the southwest of France, one of the European regions where hailstorms have a higher incidence. The Association Nationale d'Etude et de Lutte contre les Fleáux Atmosphériques (ANELFA) maintains there a dense hailpad network in continuous operation, which has created an extensive database of hail events, used in this study as ground truth. The new technique is aimed to classify the spatial distribution of different stability indexes on hail days. These indexes were calculated from vertical profiles at 1200 UTC provided by WRF numerical model, validated with radiosonde data from Bordeaux. Binary logistic regression is used to select those indexes that best represent thermodynamic conditions related to occurrence of hail in the zone. Then, they are combined in a single algorithm that surpassed the predictive power they have when used independently. Regression equation results in hail days are used in cluster analysis to identify different spatial patterns given by the probability algorithm. This new tool can be used in operational forecasting, in combination with synoptic and mesoscale techniques, to properly define hail probability and distribution. Acknowledgements The authors would like to thank the CEPA González Díez Foundation and the University of Leon for its financial support.

Quantification of Reflection Patterns in Ground-Penetrating Radar Data

NASA Astrophysics Data System (ADS)

Moysey, S.; Knight, R. J.; Jol, H. M.; Allen-King, R. M.; Gaylord, D. R.

2005-12-01

Radar facies analysis provides a way of interpreting the large-scale structure of the subsurface from ground-penetrating radar (GPR) data. Radar facies are often distinguished from each other by the presence of patterns, such as flat-lying, dipping, or chaotic reflections, in different regions of a radar image. When these patterns can be associated with radar facies in a repeated and predictable manner we refer to them as `radar textures'. While it is often possible to qualitatively differentiate between radar textures visually, pattern recognition tools, like neural networks, require a quantitative measure to discriminate between them. We investigate whether currently available tools, such as instantaneous attributes or metrics adapted from standard texture analysis techniques, can be used to improve the classification of radar facies. To this end, we use a neural network to perform cross-validation tests that assess the efficacy of different textural measures for classifying radar facies in GPR data collected from the William River delta, Saskatchewan, Canada. We found that the highest classification accuracies (>93%) were obtained for measures of texture that preserve information about the spatial arrangement of reflections in the radar image, e.g., spatial covariance. Lower accuracy (87%) was obtained for classifications based directly on windows of amplitude data extracted from the radar image. Measures that did not account for the spatial arrangement of reflections in the image, e.g., instantaneous attributes and amplitude variance, yielded classification accuracies of less than 65%. Optimal classifications were obtained for textural measures that extracted sufficient information from the radar data to discriminate between radar facies but were insensitive to other facies specific characteristics. For example, the rotationally invariant Fourier-Mellin transform delivered better classification results than the spatial covariance because dip angle of the reflections, but not dip direction, was an important discriminator between radar facies at the William River delta. To extend the use of radar texture beyond the identification of radar facies to sedimentary facies we are investigating how sedimentary features are encoded in GPR data at Borden, Ontario, Canada. At this site, we have collected extensive sedimentary and hydrologic data over the area imaged by GPR. Analysis of this data coupled with synthetic modeling of the radar signal has allowed us to develop insight into the generation of radar texture in complex geologic environments.

Simulating the Effects of Alternative Forest Management Strategies on Landscape Structure

Treesearch

Eric J. Gustafson; Thomas Crow

1996-01-01

Quantitative, spatial tools are needed to assess the long-term spatial consequences of alternative management strategies for land use planning and resource management. We constructed a timber harvest allocation model (HARVEST) that provides a visual and quantitative means to predict the spatial pattern of forest openings produced by alternative harvest strategies....

Spatial discretization of large watersheds and its influence on the estimation of hillslope sediment yield

USDA-ARS?s Scientific Manuscript database

The combined use of water erosion models and geographic information systems (GIS) has facilitated soil loss estimation at the watershed scale. Tools such as the Geo-spatial interface for the Water Erosion Prediction Project (GeoWEPP) model provide a convenient spatially distributed soil loss estimat...

Spatial fuel data products of the LANDFIRE Project

Treesearch

Matt Reeves; Kevin C. Ryan; Matthew G. Rollins; Thomas G. Thompson

2009-01-01

The Landscape Fire and Resource Management Planning Tools (LANDFIRE) Project is mapping wildland fuels, vegetation, and fire regime characteristics across the United States. The LANDFIRE project is unique because of its national scope, creating an integrated product suite at 30-m spatial resolution and complete spatial coverage of all lands within the 50...

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.

The Monitoring Erosion of Agricultural Land and spatial database of erosion events

NASA Astrophysics Data System (ADS)

Kapicka, Jiri; Zizala, Daniel

2013-04-01

In 2011 originated in The Czech Republic The Monitoring Erosion of Agricultural Land as joint project of State Land Office (SLO) and Research Institute for Soil and Water Conservation (RISWC). The aim of the project is collecting and record keeping information about erosion events on agricultural land and their evaluation. The main idea is a creation of a spatial database that will be source of data and information for evaluation and modeling erosion process, for proposal of preventive measures and measures to reduce negative impacts of erosion events. A subject of monitoring is the manifestations of water erosion, wind erosion and slope deformation in which cause damaged agriculture land. A website, available on http://me.vumop.cz, is used as a tool for keeping and browsing information about monitored events. SLO employees carry out record keeping. RISWC is specialist institute in the Monitoring Erosion of Agricultural Land that performs keeping the spatial database, running the website, managing the record keeping of events, analysis the cause of origins events and statistical evaluations of keeping events and proposed measures. Records are inserted into the database using the user interface of the website which has map server as a component. Website is based on database technology PostgreSQL with superstructure PostGIS and MapServer UMN. Each record is in the database spatial localized by a drawing and it contains description information about character of event (data, situation description etc.) then there are recorded information about land cover and about grown crops. A part of database is photodocumentation which is taken in field reconnaissance which is performed within two days after notify of event. Another part of database are information about precipitations from accessible precipitation gauges. Website allows to do simple spatial analysis as are area calculation, slope calculation, percentage representation of GAEC etc.. Database structure was designed on the base of needs analysis inputs to mathematical models. Mathematical models are used for detailed analysis of chosen erosion events which include soil analysis. Till the end 2012 has had the database 135 events. The content of database still accrues and gives rise to the extensive source of data that is usable for testing mathematical models.

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.

Collimating slicer for optical integral field spectroscopy

NASA Astrophysics Data System (ADS)

Laurent, Florence; Hénault, François

2016-07-01

Integral Field Spectroscopy (IFS) is a technique that gives simultaneously the spectrum of each spatial sampling element of a given field. It is a powerful tool which rearranges the data cube represented by two spatial dimensions defining the field and the spectral decomposition (x, y, λ) in a detector plane. In IFS, the "spatial" unit reorganizes the field, the "spectral" unit is being composed of a classical spectrograph. For the spatial unit, three main techniques - microlens array, microlens array associated with fibres and image slicer - are used in astronomical instrumentations. The development of a Collimating Slicer is to propose a new type of optical integral field spectroscopy which should be more compact. The main idea is to combine the image slicer with the collimator of the spectrograph mixing the "spatial" and "spectral" units. The traditional combination of slicer, pupil and slit elements and spectrograph collimator is replaced by a new one composed of a slicer and spectrograph collimator only. After testing few configurations, this new system looks very promising for low resolution spectrographs. In this paper, the state of art of integral field spectroscopy using image slicers will be described. The new system based onto the development of a Collimating Slicer for optical integral field spectroscopy will be depicted. First system analysis results and future improvements will be discussed.

Different Dimensions of Cognitive Style in Typical and Atypical Cognition: New Evidence and a New Measurement Tool.

PubMed

Mealor, Andy D; Simner, Julia; Rothen, Nicolas; Carmichael, Duncan A; Ward, Jamie

2016-01-01

We developed the Sussex Cognitive Styles Questionnaire (SCSQ) to investigate visual and verbal processing preferences and incorporate global/local processing orientations and systemising into a single, comprehensive measure. In Study 1 (N = 1542), factor analysis revealed six reliable subscales to the final 60 item questionnaire: Imagery Ability (relating to the use of visual mental imagery in everyday life); Technical/Spatial (relating to spatial mental imagery, and numerical and technical cognition); Language & Word Forms; Need for Organisation; Global Bias; and Systemising Tendency. Thus, we replicate previous findings that visual and verbal styles are separable, and that types of imagery can be subdivided. We extend previous research by showing that spatial imagery clusters with other abstract cognitive skills, and demonstrate that global/local bias can be separated from systemising. Study 2 validated the Technical/Spatial and Language & Word Forms factors by showing that they affect performance on memory tasks. In Study 3, we validated Imagery Ability, Technical/Spatial, Language & Word Forms, Global Bias, and Systemising Tendency by issuing the SCSQ to a sample of synaesthetes (N = 121) who report atypical cognitive profiles on these subscales. Thus, the SCSQ consolidates research from traditionally disparate areas of cognitive science into a comprehensive cognitive style measure, which can be used in the general population, and special populations.

GIS Data Collection for Pedestrian Facilities and Furniture Using Mapinr for Android

NASA Astrophysics Data System (ADS)

Naharudin, N.; Ahamad, M. S. S.; Sadullah, A. F. M.

2016-09-01

Mobile GIS is introduced to reduce the time taken in completing the field data collection procedure. With the expansion of technology today, mobile GIS is not far behind. It can be integrated with the high-end innovation tools like smartphones. Spatial data capture which deemed to be the toughest stage of a GIS project is made simple with this method. Many studies had demonstrated the usage of mobile GIS in collecting spatial data and this paper discusses how it can be applied in capturing the GPS location of pedestrian furniture and facilities. Although some of the spatial data are available from local agencies, still a more detailed data is needed to create a better data model for this study. This study uses a free android application, MAPinr, which is available on the Google PlayStore to collect spatial data on site. It adopted the GNSS and cellular network positioning to locate the position of the required data. As the application allows the captured data to be exported to a GIS platform, the geometric error of the data was improved. In the end, an authenticated spatial dataset comprising pedestrian facilities and furniture in point and line form will be produced and later be used in a pedestrian network analysis study.

Spatial decorrelation stretch of annual (2003-2014) Daymet precipitation summaries on a 1-km grid for California, Nevada, Arizona, and Utah.

PubMed

Ch Miliaresis, George

2016-06-01

A method is presented for elevation (H) and spatial position (X, Y) decorrelation stretch of annual precipitation summaries on a 1-km grid for SW USA for the period 2003 to 2014. Multiple linear regression analysis of the first and second principal component (PC) quantifies the variance in the multi-temporal precipitation imagery that is explained by X, Y, and elevation (h). The multi-temporal dataset is reconstructed from the PC1 and PC2 residual images and the later PCs by taking into account the variance that is not related to X, Y, and h. Clustering of the reconstructed precipitation dataset allowed the definition of positive (for example, in Sierra Nevada, Salt Lake City) and negative (for example, in San Joaquin Valley, Nevada, Colorado Plateau) precipitation anomalies. The temporal and spatial patterns defined from the spatially standardized multi-temporal precipitation imagery provide a tool of comparison for regions in different geographic environments according to the deviation from the precipitation amount that they are expected to receive as function of X, Y, and h. Such a standardization allows the definition of less or more sensitive to climatic change regions and gives an insight in the spatial impact of atmospheric circulation that causes the annual precipitation.

Correction of Spatial Bias in Oligonucleotide Array Data

PubMed Central

Lemieux, Sébastien

2013-01-01

Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias. PMID:23573083

Different Dimensions of Cognitive Style in Typical and Atypical Cognition: New Evidence and a New Measurement Tool

PubMed Central

Mealor, Andy D.; Simner, Julia; Rothen, Nicolas; Carmichael, Duncan A.; Ward, Jamie

2016-01-01

We developed the Sussex Cognitive Styles Questionnaire (SCSQ) to investigate visual and verbal processing preferences and incorporate global/local processing orientations and systemising into a single, comprehensive measure. In Study 1 (N = 1542), factor analysis revealed six reliable subscales to the final 60 item questionnaire: Imagery Ability (relating to the use of visual mental imagery in everyday life); Technical/Spatial (relating to spatial mental imagery, and numerical and technical cognition); Language & Word Forms; Need for Organisation; Global Bias; and Systemising Tendency. Thus, we replicate previous findings that visual and verbal styles are separable, and that types of imagery can be subdivided. We extend previous research by showing that spatial imagery clusters with other abstract cognitive skills, and demonstrate that global/local bias can be separated from systemising. Study 2 validated the Technical/Spatial and Language & Word Forms factors by showing that they affect performance on memory tasks. In Study 3, we validated Imagery Ability, Technical/Spatial, Language & Word Forms, Global Bias, and Systemising Tendency by issuing the SCSQ to a sample of synaesthetes (N = 121) who report atypical cognitive profiles on these subscales. Thus, the SCSQ consolidates research from traditionally disparate areas of cognitive science into a comprehensive cognitive style measure, which can be used in the general population, and special populations. PMID:27191169