Advances in spatial epidemiology and geographic information systems.

PubMed

Kirby, Russell S; Delmelle, Eric; Eberth, Jan M

2017-01-01

The field of spatial epidemiology has evolved rapidly in the past 2 decades. This study serves as a brief introduction to spatial epidemiology and the use of geographic information systems in applied research in epidemiology. We highlight technical developments and highlight opportunities to apply spatial analytic methods in epidemiologic research, focusing on methodologies involving geocoding, distance estimation, residential mobility, record linkage and data integration, spatial and spatio-temporal clustering, small area estimation, and Bayesian applications to disease mapping. The articles included in this issue incorporate many of these methods into their study designs and analytical frameworks. It is our hope that these studies will spur further development and utilization of spatial analysis and geographic information systems in epidemiologic research. Copyright © 2016 Elsevier Inc. All rights reserved.

[Human body meridian spatial decision support system for clinical treatment and teaching of acupuncture and moxibustion].

PubMed

Wu, Dehua

2016-01-01

The spatial position and distribution of human body meridian are expressed limitedly in the decision support system (DSS) of acupuncture and moxibustion at present, which leads to the failure to give the effective quantitative analysis on the spatial range and the difficulty for the decision-maker to provide a realistic spatial decision environment. Focusing on the limit spatial expression in DSS of acupuncture and moxibustion, it was proposed that on the basis of the geographic information system, in association of DSS technology, the design idea was developed on the human body meridian spatial DSS. With the 4-layer service-oriented architecture adopted, the data center integrated development platform was taken as the system development environment. The hierarchical organization was done for the spatial data of human body meridian via the directory tree. The structured query language (SQL) server was used to achieve the unified management of spatial data and attribute data. The technologies of architecture, configuration and plug-in development model were integrated to achieve the data inquiry, buffer analysis and program evaluation of the human body meridian spatial DSS. The research results show that the human body meridian spatial DSS could reflect realistically the spatial characteristics of the spatial position and distribution of human body meridian and met the constantly changeable demand of users. It has the powerful spatial analysis function and assists with the scientific decision in clinical treatment and teaching of acupuncture and moxibustion. It is the new attempt to the informatization research of human body meridian.

Sex Differences in Spatial Performance in the Elderly: A Review of the Literature and Suggestions for Research

ERIC Educational Resources Information Center

Cohen, Donna

1977-01-01

This paper reviews the literature on sex differences in spatial performance in older persons, proposes a theory of measurement, operational psychogenetic structuralism, for the analysis of sex differences in cognition, and suggests research directions relevant to educational gerontology. (Author)

Students’ Errors in Geometry Viewed from Spatial Intelligence

NASA Astrophysics Data System (ADS)

Riastuti, N.; Mardiyana, M.; Pramudya, I.

2017-09-01

Geometry is one of the difficult materials because students must have ability to visualize, describe images, draw shapes, and know the kind of shapes. This study aim is to describe student error based on Newmans’ Error Analysis in solving geometry problems viewed from spatial intelligence. This research uses descriptive qualitative method by using purposive sampling technique. The datas in this research are the result of geometri material test and interview by the 8th graders of Junior High School in Indonesia. The results of this study show that in each category of spatial intelligence has a different type of error in solving the problem on the material geometry. Errors are mostly made by students with low spatial intelligence because they have deficiencies in visual abilities. Analysis of student error viewed from spatial intelligence is expected to help students do reflection in solving the problem of geometry.

Spatial and Activities Models of Airport Based on GIS and Dynamic Model

NASA Astrophysics Data System (ADS)

Masri, R. M.; Purwaamijaya, I. M.

2017-02-01

The purpose of research were (1) a conceptual, functional model designed and implementation for spatial airports, (2) a causal, flow diagrams and mathematical equations made for airport activity, (3) obtained information on the conditions of space and activities at airports assessment, (4) the space and activities evaluation at airports based on national and international airport services standards, (5) options provided to improve the spatial and airport activities performance become the international standards airport. Descriptive method is used for the research. Husein Sastranegara Airport in Bandung, West Java, Indonesia was study location. The research was conducted on September 2015 to April 2016. A spatial analysis is used to obtain runway, taxiway and building airport geometric information. A system analysis is used to obtain the relationship between components in airports, dynamic simulation activity at airports and information on the results tables and graphs of dynamic model. Airport national and international standard could not be fulfilled by spatial and activity existing condition of Husein Sastranegara. Idea of re-location program is proposed as problem solving for constructing new airport which could be serving international air transportation.

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.

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

Inhabiting Indianness: Colonial Culs-de-Sac

ERIC Educational Resources Information Center

Barnd, Natchee Blu

2010-01-01

This article offers original research on the national use of Indian-themed street names in residential areas, with an analysis of the content and commentary on the spatial implications. In addition to the research on the quality and quantity of such spatial markers, the author situates this data in relation to the racial composition of the…

Spatio-temporal Analysis for New York State SPARCS Data

PubMed Central

Chen, Xin; Wang, Yu; Schoenfeld, Elinor; Saltz, Mary; Saltz, Joel; Wang, Fusheng

2017-01-01

Increased accessibility of health data provides unique opportunities to discover spatio-temporal patterns of diseases. For example, New York State SPARCS (Statewide Planning and Research Cooperative System) data collects patient level detail on patient demographics, diagnoses, services, and charges for each hospital inpatient stay and outpatient visit. Such data also provides home addresses for each patient. This paper presents our preliminary work on spatial, temporal, and spatial-temporal analysis of disease patterns for New York State using SPARCS data. We analyzed spatial distribution patterns of typical diseases at ZIP code level. We performed temporal analysis of common diseases based on 12 years’ historical data. We then compared the spatial variations for diseases with different levels of clustering tendency, and studied the evolution history of such spatial patterns. Case studies based on asthma demonstrated that the discovered spatial clusters are consistent with prior studies. We visualized our spatial-temporal patterns as animations through videos. PMID:28815148

Stage acoustics for musicians: A multidimensional approach using 3D ambisonic technology

NASA Astrophysics Data System (ADS)

Guthrie, Anne

In this research, a method was outlined and tested for the use of 3D Ambisonic technology to inform stage acoustics research and design. Stage acoustics for musicians as a field has yet to benefit from recent advancements in auralization and spatial acoustic analysis. This research attempts to address common issues in stage acoustics: subjective requirements for performers in relation to feelings of support, quality of sound, and ease of ensemble playing in relation to measurable, objective characteristics that can be used to design better stage enclosures. While these issues have been addressed in previous work, this research attempts to use technological advancements to improve the resolution and realism of the testing and analysis procedures. Advancements include measurement of spatial impulse responses using a spherical microphone array, higher-order ambisonic encoding and playback for real-time performer auralization, high-resolution spatial beamforming for analysis of onstage impulse responses, and multidimensional scaling procedures to determine subjective musician preferences. The methodology for implementing these technologies into stage acoustics research is outlined in this document and initial observations regarding implications for stage enclosure design are proposed. This research provides a robust method for measuring and analyzing performer experiences on multiple stages without the costly and time-intensive process of physically surveying orchestras on different stages, with increased repeatability while maintaining a high level of immersive realism and spatial resolution. Along with implications for physical design, this method provides possibilities for virtual teaching and rehearsal, parametric modeling and co-located performance.

A Principal Components Analysis of Dynamic Spatial Memory Biases

ERIC Educational Resources Information Center

Motes, Michael A.; Hubbard, Timothy L.; Courtney, Jon R.; Rypma, Bart

2008-01-01

Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed…

The pyramid system for multiscale raster analysis

USGS Publications Warehouse

De Cola, L.; Montagne, N.

1993-01-01

Geographical research requires the management and analysis of spatial data at multiple scales. As part of the U.S. Geological Survey's global change research program a software system has been developed that reads raster data (such as an image or digital elevation model) and produces a pyramid of aggregated lattices as well as various measurements of spatial complexity. For a given raster dataset the system uses the pyramid to report: (1) mean, (2) variance, (3) a spatial autocorrelation parameter based on multiscale analysis of variance, and (4) a monofractal scaling parameter based on the analysis of isoline lengths. The system is applied to 1-km digital elevation model (DEM) data for a 256-km2 region of central California, as well as to 64 partitions of the region. PYRAMID, which offers robust descriptions of data complexity, also is used to describe the behavior of topographic aspect with scale. ?? 1993.

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.

“Spatial Energetics”: Integrating Data From GPS, Accelerometry, and GIS to Address Obesity and Inactivity

PubMed Central

James, Peter; Jankowska, Marta; Marx, Christine; Hart, Jaime E.; Berrigan, David; Kerr, Jacqueline; Hurvitz, Philip M.; Hipp, J. Aaron; Laden, Francine

2016-01-01

To address the current obesity and inactivity epidemics, public health researchers have attempted to identify spatial factors that influence physical inactivity and obesity. Technologic and methodologic developments have led to a revolutionary ability to examine dynamic, high-resolution measures of temporally matched location and behavior data through GPS, accelerometry, and GIS. These advances allow the investigation of spatial energetics, high–spatiotemporal resolution data on location and time-matched energetics, to examine how environmental characteristics, space, and time are linked to activity-related health behaviors with far more robust and detailed data than in previous work. Although the transdisciplinary field of spatial energetics demonstrates promise to provide novel insights on how individuals and populations interact with their environment, there remain significant conceptual, technical, analytical, and ethical challenges stemming from the complex data streams that spatial energetics research generates. First, it is essential to better understand what spatial energetics data represent, the relevant spatial context of analysis for these data, and if spatial energetics can establish causality for development of spatially relevant interventions. Second, there are significant technical problems for analysis of voluminous and complex data that may require development of spatially aware scalable computational infrastructures. Third, the field must come to agreement on appropriate statistical methodologies to account for multiple observations per person. Finally, these challenges must be considered within the context of maintaining participant privacy and security. This article describes gaps in current practice and understanding, and suggests solutions to move this promising area of research forward. PMID:27528538

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,...

Environmental analysis using integrated GIS and remotely sensed data - Some research needs and priorities

NASA Technical Reports Server (NTRS)

Davis, Frank W.; Quattrochi, Dale A.; Ridd, Merrill K.; Lam, Nina S.-N.; Walsh, Stephen J.

1991-01-01

This paper discusses some basic scientific issues and research needs in the joint processing of remotely sensed and GIS data for environmental analysis. Two general topics are treated in detail: (1) scale dependence of geographic data and the analysis of multiscale remotely sensed and GIS data, and (2) data transformations and information flow during data processing. The discussion of scale dependence focuses on the theory and applications of spatial autocorrelation, geostatistics, and fractals for characterizing and modeling spatial variation. Data transformations during processing are described within the larger framework of geographical analysis, encompassing sampling, cartography, remote sensing, and GIS. Development of better user interfaces between image processing, GIS, database management, and statistical software is needed to expedite research on these and other impediments to integrated analysis of remotely sensed and GIS data.

Sex differences in visual-spatial working memory: A meta-analysis.

PubMed

Voyer, Daniel; Voyer, Susan D; Saint-Aubin, Jean

2017-04-01

Visual-spatial working memory measures are widely used in clinical and experimental settings. Furthermore, it has been argued that the male advantage in spatial abilities can be explained by a sex difference in visual-spatial working memory. Therefore, sex differences in visual-spatial working memory have important implication for research, theory, and practice, but they have yet to be quantified. The present meta-analysis quantified the magnitude of sex differences in visual-spatial working memory and examined variables that might moderate them. The analysis used a set of 180 effect sizes from healthy males and females drawn from 98 samples ranging in mean age from 3 to 86 years. Multilevel meta-analysis was used on the overall data set to account for non-independent effect sizes. The data also were analyzed in separate task subgroups by means of multilevel and mixed-effects models. Results showed a small but significant male advantage (mean d = 0.155, 95 % confidence interval = 0.087-0.223). All the tasks produced a male advantage, except for memory for location, where a female advantage emerged. Age of the participants was a significant moderator, indicating that sex differences in visual-spatial working memory appeared first in the 13-17 years age group. Removing memory for location tasks from the sample affected the pattern of significant moderators. The present results indicate a male advantage in visual-spatial working memory, although age and specific task modulate the magnitude and direction of the effects. Implications for clinical applications, cognitive model building, and experimental research are discussed.

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

PubMed

Mesman, Jessica

2009-12-01

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

Predictive mapping of forest composition and structure with direct gradient analysis and nearest neighbor imputation in coastal Oregon, U.S.A.

Treesearch

Janet L. Ohmann; Matthew J. Gregory

2002-01-01

Spatially explicit information on the species composition and structure of forest vegetation is needed at broad spatial scales for natural resource policy analysis and ecological research. We present a method for predictive vegetation mapping that applies direct gradient analysis and nearest-neighbor imputation to ascribe detailed ground attributes of vegetation to...

Spatial Integration Analysis of Provincial Historical and Cultural Heritage Resources Based on Geographic Information System (gis) — a Case Study of Spatial Integration Analysis of Historical and Cultural Heritage Resources in Zhejiang Province

NASA Astrophysics Data System (ADS)

Luo, W.; Zhang, J.; Wu, Q.; Chen, J.; Huo, X.; Zhang, J.; Zhang, Y.; Wang, T.

2017-08-01

In China historical and cultural heritage resources include historically and culturally famous cities, towns, villages, blocks, immovable cultural relics and the scenic spots with cultural connotation. The spatial distribution laws of these resources are always directly connected to the regional physical geography, historical development and historical traffic geography and have high research values. Meanwhile, the exhibition and use of these resources are greatly influenced by traffic and tourism and other plans at the provincial level, and it is of great realistic significance to offer proposals on traffic and so on that are beneficial to the exhibition of heritage resources based on the research of province distribution laws. This paper takes the spatial analysis of Geographic Information System (GIS) as the basic technological means and all historical and cultural resources in China's Zhejiang Province as research objects, and finds out in the space the accumulation areas and accumulation belts of Zhejiang Province's historic cities and cultural resources through overlay analysis and density analysis, etc. It then discusses the reasons of the formation of these accumulation areas and accumulation belts by combining with the analysis of physical geography and historical geography and so on, and in the end, linking the tourism planning and traffic planning at the provincial level, it provides suggestions on the exhibition and use of accumulation areas and accumulation belts of historic cities and cultural resources.

The geography of solar energy in the United States: Market definition, industry structure, and choice in solar PV adoption

DOE PAGES

O’Shaughnessy, Eric; Nemet, Gregory F.; Darghouth, Naïm

2018-01-30

The solar photovoltaic (PV) installation industry comprises thousands of firms around the world who collectively installed nearly 200 million panels in 2015. Spatial analysis of the emerging industry has received considerable attention from the literature, especially on the demand side concerning peer effects and adopter clustering. However this research area does not include similarly sophisticated spatial analysis on the supply side of the installation industry. The lack of understanding of the spatial structure of the PV installation industry leaves PV market research to rely on jurisdictional lines, such as counties, to define geographic PV markets. We develop an approach thatmore » uses the spatial distribution of installers' activity to define geographic boundaries for PV markets. Our method is useful for PV market research and applicable in the contexts of other industries. We use our approach to demonstrate that the PV industry in the United States is spatially heterogeneous. Despite the emergence of some national-scale PV installers, installers are largely local and installer communities are unique from one region to the next. The social implications of the spatial heterogeneity of the emerging PV industry involve improving understanding of issues such as market power, industry consolidation, and how much choice potential adopters have.« less

The geography of solar energy in the United States: Market definition, industry structure, and choice in solar PV adoption

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

O’Shaughnessy, Eric; Nemet, Gregory F.; Darghouth, Naïm

The solar photovoltaic (PV) installation industry comprises thousands of firms around the world who collectively installed nearly 200 million panels in 2015. Spatial analysis of the emerging industry has received considerable attention from the literature, especially on the demand side concerning peer effects and adopter clustering. However this research area does not include similarly sophisticated spatial analysis on the supply side of the installation industry. The lack of understanding of the spatial structure of the PV installation industry leaves PV market research to rely on jurisdictional lines, such as counties, to define geographic PV markets. We develop an approach thatmore » uses the spatial distribution of installers' activity to define geographic boundaries for PV markets. Our method is useful for PV market research and applicable in the contexts of other industries. We use our approach to demonstrate that the PV industry in the United States is spatially heterogeneous. Despite the emergence of some national-scale PV installers, installers are largely local and installer communities are unique from one region to the next. The social implications of the spatial heterogeneity of the emerging PV industry involve improving understanding of issues such as market power, industry consolidation, and how much choice potential adopters have.« less

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.

Land cover mapping and change detection in urban watersheds using QuickBird high spatial resolution satellite imagery

NASA Astrophysics Data System (ADS)

Hester, David Barry

The objective of this research was to develop methods for urban land cover analysis using QuickBird high spatial resolution satellite imagery. Such imagery has emerged as a rich commercially available remote sensing data source and has enjoyed high-profile broadcast news media and Internet applications, but methods of quantitative analysis have not been thoroughly explored. The research described here consists of three studies focused on the use of pan-sharpened 61-cm spatial resolution QuickBird imagery, the spatial resolution of which is the highest of any commercial satellite. In the first study, a per-pixel land cover classification method is developed for use with this imagery. This method utilizes a per-pixel classification approach to generate an accurate six-category high spatial resolution land cover map of a developing suburban area. The primary objective of the second study was to develop an accurate land cover change detection method for use with QuickBird land cover products. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and meaningful high spatial resolution land cover change analysis. The third study described here is an urban planning application of the high spatial resolution QuickBird-based land cover product developed in the first study. This work both meaningfully connects this exciting new data source to urban watershed management and makes an important empirical contribution to the study of suburban watersheds. Its analysis of residential roads and driveways as well as retail parking lots sheds valuable light on the impact of transportation-related land use on the suburban landscape. Broadly, these studies provide new methods for using state-of-the-art remote sensing data to inform land cover analysis and urban planning. These methods are widely adaptable and produce land cover products that are both meaningful and accurate. As additional high spatial resolution satellites are launched and the cost of high resolution imagery continues to decline, this research makes an important contribution to this exciting era in the science of remote sensing.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Impact of Spatial Scales on the Intercomparison of Climate Scenarios

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

Luo, Wei; Steptoe, Michael; Chang, Zheng

2017-01-01

Scenario analysis has been widely applied in climate science to understand the impact of climate change on the future human environment, but intercomparison and similarity analysis of different climate scenarios based on multiple simulation runs remain challenging. Although spatial heterogeneity plays a key role in modeling climate and human systems, little research has been performed to understand the impact of spatial variations and scales on similarity analysis of climate scenarios. To address this issue, the authors developed a geovisual analytics framework that lets users perform similarity analysis of climate scenarios from the Global Change Assessment Model (GCAM) using a hierarchicalmore » clustering approach.« less

A Geographic-Information-Systems-Based Approach to Analysis of Characteristics Predicting Student Persistence and Graduation

ERIC Educational Resources Information Center

Ousley, Chris

2010-01-01

This study sought to provide empirical evidence regarding the use of spatial analysis in enrollment management to predict persistence and graduation. The research utilized data from the 2000 U.S. Census and applicant records from The University of Arizona to study the spatial distributions of enrollments. Based on the initial results, stepwise…

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

NASA Astrophysics Data System (ADS)

Weng, Lingyan; Han, Xugao

2018-01-01

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

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

Spatial decision support system for tobacco enterprise based on spatial data mining

NASA Astrophysics Data System (ADS)

Mei, Xin; Liu, Junyi; Zhang, Xuexia; Cui, Weihong

2007-11-01

Tobacco enterprise is a special enterprise, which has strong correlation to regional geography. But in the past research and application, the combination between tobacco and GIS is limited to use digital maps to assist cigarette distribution. How to comprehensively import 3S technique and spatial data mining (SDM) to construct spatial decision support system (SDSS) of tobacco enterprise is the main research aspect in this paper. The paper concretely analyzes the GIS requirements in tobacco enterprise for planning location of production, monitoring production management and product sale at the beginning. Then holistic solution is presented and frame design for tobacco enterprise spatial decision based on SDM is given. This paper describes how to use spatial analysis and data mining to realize the spatial decision processing such as monitoring tobacco planted acreage, analyzing and planning the cigarette sale network and so on.

Socio-Spatial Analysis of Study Abroad Students' Experiences in/of Place in Morocco

ERIC Educational Resources Information Center

Pipitone, Jennifer M.; Raghavan, Chitra

2017-01-01

This article builds upon existing place-based research through the application of a socio-spatial perspective to make sense of how students' experiences in/of place shape, and are shaped by, the production of experiential learning space. Rather than focusing on the individual as the unit of analysis, this article is concerned with understanding…

Research on spatial-variant property of bistatic ISAR imaging plane of space target

NASA Astrophysics Data System (ADS)

Guo, Bao-Feng; Wang, Jun-Ling; Gao, Mei-Guo

2015-04-01

The imaging plane of inverse synthetic aperture radar (ISAR) is the projection plane of the target. When taking an image using the range-Doppler theory, the imaging plane may have a spatial-variant property, which causes the change of scatter’s projection position and results in migration through resolution cells. In this study, we focus on the spatial-variant property of the imaging plane of a three-axis-stabilized space target. The innovative contributions are as follows. 1) The target motion model in orbit is provided based on a two-body model. 2) The instantaneous imaging plane is determined by the method of vector analysis. 3) Three Euler angles are introduced to describe the spatial-variant property of the imaging plane, and the image quality is analyzed. The simulation results confirm the analysis of the spatial-variant property. The research in this study is significant for the selection of the imaging segment, and provides the evidence for the following data processing and compensation algorithm. Project supported by the National Natural Science Foundation of China (Grant No. 61401024), the Shanghai Aerospace Science and Technology Innovation Foundation, China (Grant No. SAST201240), and the Basic Research Foundation of Beijing Institute of Technology (Grant No. 20140542001).

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Geographic information systems, remote sensing, and spatial analysis activities in Texas, 2002-07

USGS Publications Warehouse

Pearson, D.K.; Gary, R.H.; Wilson, Z.D.

2007-01-01

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 particularly useful when analyzing a wide variety of spatial data such as with remote sensing and spatial analysis. 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 document presents information about the technical capabilities and project activities of the U.S. Geological Survey (USGS) Texas Water Science Center (TWSC) GIS Workgroup from 2002 through 2007.

An Integrative Platform for Three-dimensional Quantitative Analysis of Spatially Heterogeneous Metastasis Landscapes

NASA Astrophysics Data System (ADS)

Guldner, Ian H.; Yang, Lin; Cowdrick, Kyle R.; Wang, Qingfei; Alvarez Barrios, Wendy V.; Zellmer, Victoria R.; Zhang, Yizhe; Host, Misha; Liu, Fang; Chen, Danny Z.; Zhang, Siyuan

2016-04-01

Metastatic microenvironments are spatially and compositionally heterogeneous. This seemingly stochastic heterogeneity provides researchers great challenges in elucidating factors that determine metastatic outgrowth. Herein, we develop and implement an integrative platform that will enable researchers to obtain novel insights from intricate metastatic landscapes. Our two-segment platform begins with whole tissue clearing, staining, and imaging to globally delineate metastatic landscape heterogeneity with spatial and molecular resolution. The second segment of our platform applies our custom-developed SMART 3D (Spatial filtering-based background removal and Multi-chAnnel forest classifiers-based 3D ReconsTruction), a multi-faceted image analysis pipeline, permitting quantitative interrogation of functional implications of heterogeneous metastatic landscape constituents, from subcellular features to multicellular structures, within our large three-dimensional (3D) image datasets. Coupling whole tissue imaging of brain metastasis animal models with SMART 3D, we demonstrate the capability of our integrative pipeline to reveal and quantify volumetric and spatial aspects of brain metastasis landscapes, including diverse tumor morphology, heterogeneous proliferative indices, metastasis-associated astrogliosis, and vasculature spatial distribution. Collectively, our study demonstrates the utility of our novel integrative platform to reveal and quantify the global spatial and volumetric characteristics of the 3D metastatic landscape with unparalleled accuracy, opening new opportunities for unbiased investigation of novel biological phenomena in situ.

Nick Grue | NREL

Science.gov Websites

geospatial data analysis using parallel processing High performance computing Renewable resource technical potential and supply curve analysis Spatial database utilization Rapid analysis of large geospatial datasets energy and geospatial analysis products Research Interests Rapid, web-based renewable resource analysis

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

NASA Astrophysics Data System (ADS)

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

2014-10-01

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

Examining reference frame interaction in spatial memory using a distribution analysis.

PubMed

Street, Whitney N; Wang, Ranxiao Frances

2016-02-01

Previous research showed competition among reference frames in spatial attention and language. The present studies developed a new distribution analysis to examine reference frame interactions in spatial memory. Participants viewed virtual arrays of colored pegs and were instructed to remember them either from their own perspective or from the perspective aligned with the rectangular floor. Then they made judgments of relative directions from their respective encoding orientation. Those taking the floor-axis perspective showed systematic bias in the signed errors toward their egocentric perspective, while those taking their own perspective showed no systematic bias, both for random and symmetrical object arrays. The bias toward the egocentric perspective was observed when learning a real symmetric regular object array with strong environmental cues for the aligned axis. These results indicate automatic processing of the self reference while taking the floor-axis perspective but not vice versa, and suggest that research on spatial memory needs to consider the implications of competition effects in reference frame use.

Spatial structure, sampling design and scale in remotely-sensed imagery of a California savanna woodland

NASA Technical Reports Server (NTRS)

Mcgwire, K.; Friedl, M.; Estes, J. E.

1993-01-01

This article describes research related to sampling techniques for establishing linear relations between land surface parameters and remotely-sensed data. Predictive relations are estimated between percentage tree cover in a savanna environment and a normalized difference vegetation index (NDVI) derived from the Thematic Mapper sensor. Spatial autocorrelation in original measurements and regression residuals is examined using semi-variogram analysis at several spatial resolutions. Sampling schemes are then tested to examine the effects of autocorrelation on predictive linear models in cases of small sample sizes. Regression models between image and ground data are affected by the spatial resolution of analysis. Reducing the influence of spatial autocorrelation by enforcing minimum distances between samples may also improve empirical models which relate ground parameters to satellite data.

Gendered Distances: A Methodological Inquiry into Spatial Analysis as an Instrument for Assessing Gender Equality in Access to Secondary Schools in Mukono District, Uganda

ERIC Educational Resources Information Center

Wawro, Patrick R.

2010-01-01

This study focused on how accessibility to secondary schools in the Mukono District of Uganda is related to the sex and gender of the student and the distance that separates the student's home from the school they attend. This research is a methodological inquiry exploring the use of spatial analysis, specifically how cognitive and metric…

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

PubMed

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

2014-05-01

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

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.

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...

The semantic analysis about the spatial orientation expression of GIS in Chinese case study of Beijing

NASA Astrophysics Data System (ADS)

Zhang, Jing; Liu, Yu; Sun, Jiuhu; Zhang, Jie

2006-10-01

Spatial relationship is an important research area in GIS. The orientation information about the urban environment is directly available to human beings through perception and is crucial for establishing their spatial location and for way-finding. People perceive the layout of entities in space, categorize them as spatial relationships, and describe them as spatial expression in language. The orientation expression in different language is different. This paper will discuss the road network in Beijing and its characteristic. We analyze the post-position in Chinese, we know that people like to use 'outside' and 'inside' in the sentence "N is + ring road + postposition" by first experiment. We will illustrate the fuzzy range by 'outside or inside' in the ring-road by the second experiment. In the last part, we conclude the paper and our further research.

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

Validating crash locations for quantitative spatial analysis: a GIS-based approach.

PubMed

Loo, Becky P Y

2006-09-01

In this paper, the spatial variables of the crash database in Hong Kong from 1993 to 2004 are validated. The proposed spatial data validation system makes use of three databases (the crash, road network and district board databases) and relies on GIS to carry out most of the validation steps so that the human resource required for manually checking the accuracy of the spatial data can be enormously reduced. With the GIS-based spatial data validation system, it was found that about 65-80% of the police crash records from 1993 to 2004 had correct road names and district board information. In 2004, the police crash database contained about 12.7% mistakes for road names and 9.7% mistakes for district boards. The situation was broadly comparable to the United Kingdom. However, the results also suggest that safety researchers should carefully validate spatial data in the crash database before scientific analysis.

Nitrogen Oxide Emission, Economic Growth and Urbanization in China: a Spatial Econometric Analysis

NASA Astrophysics Data System (ADS)

Zhou, Zhimin; Zhou, Yanli; Ge, Xiangyu

2018-01-01

This research studies the nexus of nitrogen oxide emissions and economic development/urbanization. Under the environmental Kuznets curve (EKC) hypothesis, we apply the analysis technique of spatial panel data in the STIRPAT framework, and thus obtain the estimated impacts of income/urbanization on nitrogen oxide emission systematically. The empirical findings suggest that spatial dependence on nitrogen oxide emission distribution exist at provincial level, and the inverse N-shape EKC describes both income-nitrogen oxide and urbanization-nitrogen oxide nexuses. In addition, some well-directed policy advices are made to reduce the nitrogen oxide emission in future.

Urbanization and Land Use Changes in Peri-Urban Area using Spatial Analysis Methods (Case Study: Ciawi Urban Areas, Bogor Regency)

NASA Astrophysics Data System (ADS)

Cahya, D. L.; Martini, E.; Kasikoen, K. M.

2018-02-01

Urbanization is shown by the increasing percentage of the population in urban areas. In Indonesia, the percentage of urban population increased dramatically form 17.42% (1971) to 42.15% (2010). This resulted in increased demand for housing. Limited land in the city area push residents looking for an alternative location of his residence to the peri-urban areas. It is accompanied by a process of land conversion from green area into built-up area. Continuous land conversion in peri-urban area is becoming increasingly widespread. Bogor Regency as part of the Jakarta Metropolitan Area is experiencing rapid development. This regency has been experienced land-use change very rapidly from agricultural areas into urban built up areas. Aim of this research is to analyze the effect of urbanization on land use changes in peri-urban areas using spatial analysis methods. This research used case study of Ciawi Urban Area that experiencing rapid development. Method of this research is using descriptive quantitative approach. Data used in this research is primary data (field survey) and secondary data (maps). To analyze land use change is using Geographic Information System (GIS) as spatial analysis methods. The effect of urbanization on land use changes in Ciawi Urban Area from year 2013 to 2015 is significant. The reduction of farm land is around -4.00% and wetland is around - 2.51%. The increasing area for hotel/villa/resort is around 3.10%. Based on this research, local government (Bogor Regency) should be alert to the land use changes that does not comply with the land use plan and also consistently apply the spatial planning.

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

NASA Astrophysics Data System (ADS)

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

2005-10-01

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

NASA Fundamental Remote Sensing Science Research Program

NASA Technical Reports Server (NTRS)

1984-01-01

The NASA Fundamental Remote Sensing Research Program is described. The program provides a dynamic scientific base which is continually broadened and from which future applied research and development can draw support. In particular, the overall objectives and current studies of the scene radiation and atmospheric effect characterization (SRAEC) project are reviewed. The SRAEC research can be generically structured into four types of activities including observation of phenomena, empirical characterization, analytical modeling, and scene radiation analysis and synthesis. The first three activities are the means by which the goal of scene radiation analysis and synthesis is achieved, and thus are considered priority activities during the early phases of the current project. Scene radiation analysis refers to the extraction of information describing the biogeophysical attributes of the scene from the spectral, spatial, and temporal radiance characteristics of the scene including the atmosphere. Scene radiation synthesis is the generation of realistic spectral, spatial, and temporal radiance values for a scene with a given set of biogeophysical attributes and atmospheric conditions.

Research on the optimization of air quality monitoring station layout based on spatial grid statistical analysis method.

PubMed

Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An

2018-05-01

In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.

Nonlinearity in Social Service Evaluation: A Primer on Agent-Based Modeling

ERIC Educational Resources Information Center

Israel, Nathaniel; Wolf-Branigin, Michael

2011-01-01

Measurement of nonlinearity in social service research and evaluation relies primarily on spatial analysis and, to a lesser extent, social network analysis. Recent advances in geographic methods and computing power, however, allow for the greater use of simulation methods. These advances now enable evaluators and researchers to simulate complex…

Usefulness of the group-comparison method to demonstrate sex differences in spatial orientation and spatial visualization in older men and women.

PubMed

Cohen, D

1976-10-01

This paper reports an analysis of sex differences in cognitive test scores covering the dimensions of spatial orientation and spatial visualization in groups of 6 older men and 6 women matched for speed of performance on a maze test and level of performance on a spatial relations task. Older men were more proficient solving spatial problems using the body as a referent, whereas there was no significant difference between the sexes in imagining spatial displacement. Matched comparisons appear a useful adjunct to population research to understand the type(s) of cognitive processes where differential performance by the sexes is observed.

Comparison of Urban Human Movements Inferring from Multi-Source Spatial-Temporal Data

NASA Astrophysics Data System (ADS)

Cao, Rui; Tu, Wei; Cao, Jinzhou; Li, Qingquan

2016-06-01

The quantification of human movements is very hard because of the sparsity of traditional data and the labour intensive of the data collecting process. Recently, much spatial-temporal data give us an opportunity to observe human movement. This research investigates the relationship of city-wide human movements inferring from two types of spatial-temporal data at traffic analysis zone (TAZ) level. The first type of human movement is inferred from long-time smart card transaction data recording the boarding actions. The second type of human movement is extracted from citywide time sequenced mobile phone data with 30 minutes interval. Travel volume, travel distance and travel time are used to measure aggregated human movements in the city. To further examine the relationship between the two types of inferred movements, the linear correlation analysis is conducted on the hourly travel volume. The obtained results show that human movements inferred from smart card data and mobile phone data have a correlation of 0.635. However, there are still some non-ignorable differences in some special areas. This research not only reveals the citywide spatial-temporal human dynamic but also benefits the understanding of the reliability of the inference of human movements with big spatial-temporal data.

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

PubMed Central

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

2015-01-01

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

An innovative expression model of human health risk based on the quantitative analysis of soil metals sources contribution in different spatial scales.

PubMed

Zhang, Yimei; Li, Shuai; Wang, Fei; Chen, Zhuang; Chen, Jie; Wang, Liqun

2018-09-01

Toxicity of heavy metals from industrialization poses critical concern, and analysis of sources associated with potential human health risks is of unique significance. Assessing human health risk of pollution sources (factored health risk) concurrently in the whole and the sub region can provide more instructive information to protect specific potential victims. In this research, we establish a new expression model of human health risk based on quantitative analysis of sources contribution in different spatial scales. The larger scale grids and their spatial codes are used to initially identify the level of pollution risk, the type of pollution source and the sensitive population at high risk. The smaller scale grids and their spatial codes are used to identify the contribution of various sources of pollution to each sub region (larger grid) and to assess the health risks posed by each source for each sub region. The results of case study show that, for children (sensitive populations, taking school and residential area as major region of activity), the major pollution source is from the abandoned lead-acid battery plant (ALP), traffic emission and agricultural activity. The new models and results of this research present effective spatial information and useful model for quantifying the hazards of source categories and human health a t complex industrial system in the future. Copyright © 2018 Elsevier Ltd. All rights reserved.

A principal components analysis of dynamic spatial memory biases.

PubMed

Motes, Michael A; Hubbard, Timothy L; Courtney, Jon R; Rypma, Bart

2008-09-01

Research has shown that spatial memory for moving targets is often biased in the direction of implied momentum and implied gravity, suggesting that representations of the subjective experiences of these physical principles contribute to such biases. The present study examined the association between these spatial memory biases. Observers viewed targets that moved horizontally from left to right before disappearing or viewed briefly shown stationary targets. After a target disappeared, observers indicated the vanishing position of the target. Principal components analysis revealed that biases along the horizontal axis of motion loaded on separate components from biases along the vertical axis orthogonal to motion. The findings support the hypothesis that implied momentum and implied gravity biases have unique influences on spatial memory. (c) 2008 APA, all rights reserved.

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

PubMed

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

2008-07-01

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

Dynamic Analysis and Research on Environmental Pollution in China from 1992 to 2014

NASA Astrophysics Data System (ADS)

Sun, Fei; Yuan, Peng; Li, Huiting; Zhang, Moli

2018-01-01

The regular pattern of development of the environmental pollution events was analyzed from the perspective of statistical analysis of pollution events in recent years. The Moran, s I and spatial center-of-gravity shift curve of China, s environmental emergencies were calculated by ARCGIS software. And the method is global spatial analysis and spatial center of gravity shift. The results showed that the trend of China, s environmental pollution events from 1992 to 2014 was the first dynamic growth and then gradually reduced. Environmental pollution events showed spatial aggregation distribution in 1992-1994, 2001-2006, 2008-2014, and the rest of year was a random distribution of space. There were two stages in China, s environmental pollution events: The transition to the southwest from 1992 to 2006 and the transition to the northeast from the year of 2006 to 2014.

The modifiable areal unit problem (MAUP) in the relationship between exposure to NO2 and respiratory health

PubMed Central

2011-01-01

Background Many Canadian population health studies, including those focusing on the relationship between exposure to air pollution and health, have operationalized neighbourhoods at the census tract scale. At the same time, the conceptualization of place at the local scale is one of the weakest theoretical aspects in health geography. The modifiable areal unit problem (MAUP) raises issues when census tracts are used as neighbourhood proxies, and no other alternate spatial structure is used for sensitivity analysis. In the literature, conclusions on the relationship between NO2 and health outcomes are divided, and this situation may in part be due to the selection of an inappropriate spatial structure for analysis. Here, we undertake an analysis of NO2 and respiratory health in Ottawa, Canada using three different spatial structures in order to elucidate the effects that the spatial unit of analysis can have on analytical results. Results Using three different spatial structures to examine and quantify the relationship between NO2 and respiratory morbidity, we offer three main conclusions: 1) exploratory spatial analytical methods can serve as an indication of the potential effect of the MAUP; 2) OLS regression results differ significantly using different spatial representations, and this could be a contributing factor to the lack of consensus in studies that focus on the relation between NO2 and respiratory health at the area-level; and 3) the use of three spatial representations confirms no measured effect of NO2 exposure on respiratory health in Ottawa. Conclusions Area units used in population health studies should be delineated so as to represent the a priori scale of the expected scale interaction between neighbourhood processes and health. A thorough understanding of the role of the MAUP in the study of the relationship between NO2 and respiratory health is necessary for research into disease pathways based on statistical models, and for decision-makers to assess the scale at which interventions will have maximum benefit. In general, more research on the role of spatial representation in health studies is needed. PMID:22040001

Mapping and modeling the urban landscape in Bangkok, Thailand: Physical-spectral-spatial relations of population-environmental interactions

NASA Astrophysics Data System (ADS)

Shao, Yang

This research focuses on the application of remote sensing, geographic information systems, statistical modeling, and spatial analysis to examine the dynamics of urban land cover, urban structure, and population-environment interactions in Bangkok, Thailand, with an emphasis on rural-to-urban migration from rural Nang Rong District, Northeast Thailand to the primate city of Bangkok. The dissertation consists of four main sections: (1) development of remote sensing image classification and change-detection methods for characterizing imperviousness for Bangkok, Thailand from 1993-2002; (2) development of 3-D urban mapping methods, using high spatial resolution IKONOS satellite images, to assess high-rises and other urban structures; (3) assessment of urban spatial structure from 2-D and 3-D perspectives; and (4) an analysis of the spatial clustering of migrants from Nang Rong District in Bangkok and the neighborhood environments of migrants' locations. Techniques are developed to improve the accuracy of the neural network classification approach for the analysis of remote sensing data, with an emphasis on the spectral unmixing problem. The 3-D building heights are derived using the shadow information on the high-resolution IKONOS image. The results from the 2-D and 3-D mapping are further examined to assess urban structure and urban feature identification. This research contributes to image processing of remotely-sensed images and urban studies. The rural-urban migration process and migrants' settlement patterns are examined using spatial statistics, GIS, and remote sensing perspectives. The results show that migrants' spatial clustering in urban space is associated with the source village and a number of socio-demographic variables. In addition, the migrants' neighborhood environments in urban setting are modeled using a set of geographic and socio-demographic variables, and the results are scale-dependent.

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.

Analysis of students geometry skills viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Riastuti, Nova; Mardiyana, Pramudya, Ikrar

2017-12-01

Geometry is one of the difficult materials for students because students must have the ability to visualize, describe the picture, draw a figure, and know the kinds of figures. This study aimisto describe the students geometry skills in resolving geometry problems viewed from spatial intelligence. This research uses a descriptive qualitative method has aim to identify students geometry skills by 6 students in eight grade of Ngawi regency, Indonesia. The subjects were 2 students with high spatial intelligence, 2 students with medium spatial intelligence, and 2 students with low spatial intelligence. Datas were collected based on written test and interview. The result of this research showed that the students geometry skills viewed from spatial intelligence includes. The results of this study indicate that there was a correlation between students' spatial intelligence with geometric skills. Students had different geometric skills in each category of spatial intelligence, although there were similarities in some geometry skill indicators. Students with low spatial intelligence had less geometry skills, thus requiring special attention from teachers. Mathematics teachers are expected to provide more practice questions that reinforce students' geometry skills including visual skills, descriptive skills, drawing skills, logical skills, applied skills.

The emergence of spatial cyberinfrastructure.

PubMed

Wright, Dawn J; Wang, Shaowen

2011-04-05

Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge.

The emergence of spatial cyberinfrastructure

PubMed Central

Wright, Dawn J.; Wang, Shaowen

2011-01-01

Cyberinfrastructure integrates advanced computer, information, and communication technologies to empower computation-based and data-driven scientific practice and improve the synthesis and analysis of scientific data in a collaborative and shared fashion. As such, it now represents a paradigm shift in scientific research that has facilitated easy access to computational utilities and streamlined collaboration across distance and disciplines, thereby enabling scientific breakthroughs to be reached more quickly and efficiently. Spatial cyberinfrastructure seeks to resolve longstanding complex problems of handling and analyzing massive and heterogeneous spatial datasets as well as the necessity and benefits of sharing spatial data flexibly and securely. This article provides an overview and potential future directions of spatial cyberinfrastructure. The remaining four articles of the special feature are introduced and situated in the context of providing empirical examples of how spatial cyberinfrastructure is extending and enhancing scientific practice for improved synthesis and analysis of both physical and social science data. The primary focus of the articles is spatial analyses using distributed and high-performance computing, sensor networks, and other advanced information technology capabilities to transform massive spatial datasets into insights and knowledge. PMID:21467227

Linking Temporal-Optimization and Spatial-Simulation Models for Forest Planning

Treesearch

Larry A. Leefers; Eric J. Gustafson; Phillip Freeman

2003-01-01

Increasingly, resource management agencies and researchers have turned their analysis and modeling efforts towards spatial and temporal information. This is driven by the need to address wildlife concerns, landscape issues, and social/economic questions. Historically, the USDA Forest Service has used optimization models (i.e., FORPLAN and Spectrum) for timber harvest...

Forest Ecosystem Analysis Using a GIS

Treesearch

S.G. McNulty; W.T. Swank

1996-01-01

Forest ecosystem studies have expanded spatially in recent years to address large scale environmental issues. We are using a geographic information system (GIS) to understand and integrate forest processes at landscape to regional spatial scales. This paper presents three diverse research studies using a GIS. First, we used a GIS to develop a landscape scale model to...

Application of spatial technology in malaria research & control: some new insights.

PubMed

Saxena, Rekha; Nagpal, B N; Srivastava, Aruna; Gupta, S K; Dash, A P

2009-08-01

Geographical information System (GIS) has emerged as the core of the spatial technology which integrates wide range of dataset available from different sources including Remote Sensing (RS) and Global Positioning System (GPS). Literature published during the decade (1998-2007) has been compiled and grouped into six categories according to the usage of the technology in malaria epidemiology. Different GIS modules like spatial data sources, mapping and geo-processing tools, distance calculation, digital elevation model (DEM), buffer zone and geo-statistical analysis have been investigated in detail, illustrated with examples as per the derived results. These GIS tools have contributed immensely in understanding the epidemiological processes of malaria and examples drawn have shown that GIS is now widely used for research and decision making in malaria control. Statistical data analysis currently is the most consistent and established set of tools to analyze spatial datasets. The desired future development of GIS is in line with the utilization of geo-statistical tools which combined with high quality data has capability to provide new insight into malaria epidemiology and the complexity of its transmission potential in endemic areas.

Analysis of Coastal Dunes: A Remote Sensing and Statistical Approach.

ERIC Educational Resources Information Center

Jones, J. Richard

1985-01-01

Remote sensing analysis and statistical methods were used to analyze the coastal dunes of Plum Island, Massachusetts. The research methodology used provides an example of a student project for remote sensing, geomorphology, or spatial analysis courses at the university level. (RM)

[Assessment on ecological security spatial differences of west areas of Liaohe River based on GIS].

PubMed

Wang, Geng; Wu, Wei

2005-09-01

Ecological security assessment and early warning research have spatiality; non-linearity; randomicity, it is needed to deal with much spatial information. Spatial analysis and data management are advantages of GIS, it can define distribution trend and spatial relations of environmental factors, and show ecological security pattern graphically. The paper discusses the method of ecological security spatial differences of west areas of Liaohe River based on GIS and ecosystem non-health. First, studying on pressure-state-response (P-S-R) assessment indicators system, investigating in person and gathering information; Second, digitizing the river, applying fuzzy AHP to put weight, quantizing and calculating by fuzzy comparing; Last, establishing grid data-base; expounding spatial differences of ecological security by GIS Interpolate and Assembly.

Using a cross section to train veterinary students to visualize anatomical structures in three dimensions

NASA Astrophysics Data System (ADS)

Provo, Judy; Lamar, Carlton; Newby, Timothy

2002-01-01

A cross section was used to enhance three-dimensional knowledge of anatomy of the canine head. All veterinary students in two successive classes (n = 124) dissected the head; experimental groups also identified structures on a cross section of the head. A test assessing spatial knowledge of the head generated 10 dependent variables from two administrations. The test had content validity and statistically significant interrater and test-retest reliability. A live-dog examination generated one additional dependent variable. Analysis of covariance controlling for performance on course examinations and quizzes revealed no treatment effect. Including spatial skill as a third covariate revealed a statistically significant effect of spatial skill on three dependent variables. Men initially had greater spatial skill than women, but spatial skills were equal after 8 months. A qualitative analysis showed the positive impact of this experience on participants. Suggestions for improvement and future research are discussed.

Lightning characteristics of derecho producing mesoscale convective systems

NASA Astrophysics Data System (ADS)

Bentley, Mace L.; Franks, John R.; Suranovic, Katelyn R.; Barbachem, Brent; Cannon, Declan; Cooper, Stonie R.

2016-06-01

Derechos, or widespread, convectively induced wind storms, are a common warm season phenomenon in the Central and Eastern United States. These damaging and severe weather events are known to sweep quickly across large spatial regions of more than 400 km and produce wind speeds exceeding 121 km h-1. Although extensive research concerning derechos and their parent mesoscale convective systems already exists, there have been few investigations of the spatial and temporal distribution of associated cloud-to-ground lightning with these events. This study analyzes twenty warm season (May through August) derecho events between 2003 and 2013 in an effort to discern their lightning characteristics. Data used in the study included cloud-to-ground flash data derived from the National Lightning Detection Network, WSR-88D imagery from the University Corporation for Atmospheric Research, and damaging wind report data obtained from the Storm Prediction Center. A spatial and temporal analysis was conducted by incorporating these data into a geographic information system to determine the distribution and lightning characteristics of the environments of derecho producing mesoscale convective systems. Primary foci of this research include: (1) finding the approximate size of the lightning activity region for individual and combined event(s); (2) determining the intensity of each event by examining the density and polarity of lightning flashes; (3) locating areas of highest lightning flash density; and (4) to provide a lightning spatial analysis that outlines the temporal and spatial distribution of flash activity for particularly strong derecho producing thunderstorm episodes.

Research on spatial difference in the effecting factors of the urban flow

NASA Astrophysics Data System (ADS)

Liang, Jian; Li, Feixue; Xu, Jiangang; Li, Manchun

2007-06-01

Urban flow is a phenomenon of the interaction and relation between the cities in the region based on the transport network and urban synthetic strength. And, because of the difference in traffic conditions and the level of economic development in different city, the intensity of the urban flow of each city is different and the primary effecting factor is dissimilar. The traditional analysis on the effecting factors of urban flow concerns the background of the entire region as a whole entity, which would be too vague and ignore the difference in the effecting factors of different cities as well as the micro differences and spatial non-stationarity in the dominant factor. The research on spatial difference in the effecting factors of the urban flow in this paper focused on the analysis of the diverse effecting factors of urban flow caused by the regional disparity; found out the primary factors; and analyzed the spatial characteristics of effecting factors using GIS. We established a mathematical model, which was applied to the urban agglomeration of the Yangtze River Delta, the intensity of the urban flow of every city in this district was figured and the regression model was constructed. The principal effecting factor of the urban flow of every city and its characteristic of the spatial distribution was analyzed. we summarized the effecting factors of the urban flow is an indication of the persistence of spatial difference among Yangtze River Delta, and the spatial pattern of it was investigated.

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.

Research on key technologies for data-interoperability-based metadata, data compression and encryption, and their application

NASA Astrophysics Data System (ADS)

Yu, Xu; Shao, Quanqin; Zhu, Yunhai; Deng, Yuejin; Yang, Haijun

2006-10-01

With the development of informationization and the separation between data management departments and application departments, spatial data sharing becomes one of the most important objectives for the spatial information infrastructure construction, and spatial metadata management system, data transmission security and data compression are the key technologies to realize spatial data sharing. This paper discusses the key technologies for metadata based on data interoperability, deeply researches the data compression algorithms such as adaptive Huffman algorithm, LZ77 and LZ78 algorithm, studies to apply digital signature technique to encrypt spatial data, which can not only identify the transmitter of spatial data, but also find timely whether the spatial data are sophisticated during the course of network transmission, and based on the analysis of symmetric encryption algorithms including 3DES,AES and asymmetric encryption algorithm - RAS, combining with HASH algorithm, presents a improved mix encryption method for spatial data. Digital signature technology and digital watermarking technology are also discussed. Then, a new solution of spatial data network distribution is put forward, which adopts three-layer architecture. Based on the framework, we give a spatial data network distribution system, which is efficient and safe, and also prove the feasibility and validity of the proposed solution.

Frames of reference for helicopter electronic maps - The relevance of spatial cognition and componential analysis

NASA Technical Reports Server (NTRS)

Harwood, Kelly; Wickens, Christopher D.

1991-01-01

Computer-generated map displays for NOE and low-level helicopter flight were formed according to prior research on maps, navigational problem solving, and spatial cognition in large-scale environments. The north-up map emphasized consistency of object location, wheareas, the track-up map emphasized map-terrain congruency. A component analysis indicates that different cognitive components, e.g., orienting and absolute object location, are supported to varying degrees by properties of different frames of reference.

Empirical Research on Spatial Diffusion Process of Knowledge Spillovers

NASA Astrophysics Data System (ADS)

Jin, Xuehui

2018-02-01

Firstly, this paper gave a brief review of the core issues of previous studies on spatial distribution of knowledge spillovers. That laid the theoretical foundation for further research. Secondly, this paper roughly described the diffusion process of solar patents in Bejing-Tianjin-Hebei and the Pearl River Delta regions by means of correlation analysis based on patent information of the application date and address of patentee. After that, this paper introduced the variables of spatial distance, knowledge absorptive capacity, knowledge gap and pollution control and built the empirical model of patent, and then collecting data to test them. The results showed that knowledge absorptive capacity was the most significant factor than the other three, followed by the knowledge gap. The influence of spatial distance on knowledge spillovers was limited and the most weak influence factor was pollution control.

D Visibility Analysis in Urban Environment - Cognition Research Based on Vge

NASA Astrophysics Data System (ADS)

Lin, T. P.; Lin, H.; Hu, M. Y.

2013-09-01

The author in this research attempts to illustrate a measurable relationship between the physical environment and human's visual perception, including the distance, visual angle impact and visual field (a 3D isovist conception) against human's cognition way, by using a 3D visibility analysis method based on the platform of Virtual Geographic Environment (VGE). The whole project carries out in the CUHK campus (the Chinese University of Hong Kong), by adopting a virtual 3D model of the whole campus and survey in real world. A possible model for the simulation of human cognition in urban spaces is expected to be the output of this research, such as what the human perceive from the environment, how their feelings and behaviours are and how they affect the surrounding world. Kevin Lynch raised 5 elements of urban design in 1960s, which are "vitality, sense, fit, access and control". As the development of urban design, several problems around the human's cognitive and behaviour have come out. Due to the restriction of sensing knowledge in urban spaces, the research among the "sense" and the "fit" of urban design were not quite concerned in recent decades. The geo-spatial cognition field comes into being in 1997 and developed in recent 15 years, which made great effort in way-finding and urban behaviour simulation based on the platform of GIS (geographic information system) or VGE. The platform of VGE is recognized as a proper tool for the analysis of human's perception in urban places, because of its efficient 3D spatial data management and excellent 3D visualization for output result. This article will generally describe the visibility analysis method based on the 3D VGE platform. According to the uncertainty and variety of human perception existed in this research, the author attempts to arrange a survey of observer investigation and validation for the analysis results. Four figures related with space and human's perception will be mainly concerned in this proposal: openness, permeability, environmental pressure and visibility, and these will also be used as the identification for different type of spaces. Generally, the author is aiming at contributing a possible way to understand the reason of human's cognition in geo-spatial area, and provides efficient mathematical model between spatial information and visual perception to the related research field.

Temporal and spatial analysis of psittacosis in association with poultry farming in the Netherlands, 2000-2015.

PubMed

Hogerwerf, Lenny; Holstege, Manon M C; Benincà, Elisa; Dijkstra, Frederika; van der Hoek, Wim

2017-07-26

Human psittacosis is a highly under diagnosed zoonotic disease, commonly linked to psittacine birds. Psittacosis in birds, also known as avian chlamydiosis, is endemic in poultry, but the risk for people living close to poultry farms is unknown. Therefore, our study aimed to explore the temporal and spatial patterns of human psittacosis infections and identify possible associations with poultry farming in the Netherlands. We analysed data on 700 human cases of psittacosis notified between 01-01-2000 and 01-09-2015. First, we studied the temporal behaviour of psittacosis notifications by applying wavelet analysis. Then, to identify possible spatial patterns, we applied spatial cluster analysis. Finally, we investigated the possible spatial association between psittacosis notifications and data on the Dutch poultry sector at municipality level using a multivariable model. We found a large spatial cluster that covered a highly poultry-dense area but additional clusters were found in areas that had a low poultry density. There were marked geographical differences in the awareness of psittacosis and the amount and the type of laboratory diagnostics used for psittacosis, making it difficult to draw conclusions about the correlation between the large cluster and poultry density. The multivariable model showed that the presence of chicken processing plants and slaughter duck farms in a municipality was associated with a higher rate of human psittacosis notifications. The significance of the associations was influenced by the inclusion or exclusion of farm density in the model. Our temporal and spatial analyses showed weak associations between poultry-related variables and psittacosis notifications. Because of the low number of psittacosis notifications available for analysis, the power of our analysis was relative low. Because of the exploratory nature of this research, the associations found cannot be interpreted as evidence for airborne transmission of psittacosis from poultry to the general population. Further research is needed to determine the prevalence of C. psittaci in Dutch poultry. Also, efforts to promote PCR-based testing for C. psittaci and genotyping for source tracing are important to reduce the diagnostic deficit, and to provide better estimates of the human psittacosis burden, and the possible role of poultry.

Applications of spatially offset Raman spectroscopy to defense and security

NASA Astrophysics Data System (ADS)

Guicheteau, Jason; Hopkins, Rebecca

2016-05-01

Spatially offset Raman spectroscopy (SORS) allows for sub-surface and through barrier detection and has applications in drug analysis, cancer detection, forensic science, as well as defense and security. This paper reviews previous efforts in SORS and other through barrier Raman techniques and presents a discussion on current research in defense and security applications.

Poverty and Algebra Performance: A Comparative Spatial Analysis of a Border South State

ERIC Educational Resources Information Center

Tate, William F.; Hogrebe, Mark C.

2015-01-01

This research uses two measures of poverty, as well as mobility and selected education variables to study how their relationships vary across 543 Missouri high school districts. Using Missouri and U.S. Census American Community Survey (ACS) data, local R[superscript 2]'s from geographically weighted regressions are spatially mapped to demonstrate…

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

USGS Publications Warehouse

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

2010-01-01

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

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.

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

NASA Astrophysics Data System (ADS)

Belianinov, Alex; Ganesh, Panchapakesan; Lin, Wenzhi; Sales, Brian C.; Sefat, Athena S.; Jesse, Stephen; Pan, Minghu; Kalinin, Sergei V.

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1-xSex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.

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.

Understanding spatial organizations of chromosomes via statistical analysis of Hi-C data

PubMed Central

Hu, Ming; Deng, Ke; Qin, Zhaohui; Liu, Jun S.

2015-01-01

Understanding how chromosomes fold provides insights into the transcription regulation, hence, the functional state of the cell. Using the next generation sequencing technology, the recently developed Hi-C approach enables a global view of spatial chromatin organization in the nucleus, which substantially expands our knowledge about genome organization and function. However, due to multiple layers of biases, noises and uncertainties buried in the protocol of Hi-C experiments, analyzing and interpreting Hi-C data poses great challenges, and requires novel statistical methods to be developed. This article provides an overview of recent Hi-C studies and their impacts on biomedical research, describes major challenges in statistical analysis of Hi-C data, and discusses some perspectives for future research. PMID:26124977

Photography activities for developing students’ spatial orientation and spatial visualization

NASA Astrophysics Data System (ADS)

Hendroanto, Aan; van Galen, Frans; van Eerde, D.; Prahmana, R. C. I.; Setyawan, F.; Istiandaru, A.

2017-12-01

Spatial orientation and spatial visualization are the foundation of students’ spatial ability. They assist students’ performance in learning mathematics, especially geometry. Considering its importance, the present study aims to design activities to help young learners developing their spatial orientation and spatial visualization ability. Photography activity was chosen as the context of the activity to guide and support the students. This is a design research study consisting of three phases: 1) preparation and designing 2) teaching experiment, and 3) retrospective analysis. The data is collected by tests and interview and qualitatively analyzed. We developed two photography activities to be tested. In the teaching experiments, 30 students of SD Laboratorium UNESA, Surabaya were involved. The results showed that the activities supported the development of students’ spatial orientation and spatial visualization indicated by students’ learning progresses, answers, and strategies when they solved the problems in the activities.

Simulating air quality in the Netherlands with WRF-Chem 3.8.1 at high resolution

NASA Astrophysics Data System (ADS)

Hilboll, Andreas; Kuenen, Jeroen; Denier van der Gon, Hugo; Vrekoussis, Mihalis

2017-04-01

Air pollution is the single most important environmental hazard for public health. Especially nitrogen dioxide (NO(2)) plays a key role in air quality research, both due to its immediate importance for the production of tropospheric ozone and acid rain, and as a general indicator of fossil fuel burning. To improve the quality and reproducibility of measurements of NO(2) vertical distribution from MAX-DOAS instruments, the CINDI-2 campaign was held in Cabauw (NL) in September 2016, featuring instruments from many of the leading atmospheric research institutions in the world. The measurement site in Cabauw is located in a rather rural region, surrounded by several major pollution centers (Utrecht, Rotterdam, Amsterdam). Since the instruments measure in several azimuthal directions, the measurements are able to provide information about the high spatial and temporal variability in pollutant concentrations, caused by both the spatial heterogeneity of emissions and meteorological conditions. When using air quality models in the analysis of the measured data to identify pollution sources, this mandates high spatial resolution in order to resolve the expected fine spatial structure in NO(2) concentrations. In spite of constant advances in computing power, this remains a challenge, mostly due to the uncertainties and large spatial heterogeneity of emissions and the need to parameterize small-scale processes. In this study, we use the most recent version 3.8.1 of the Weather Research and Forecasting Model with Chemistry (WRF-Chem) to simulate air pollutant concentrations over the Netherlands, to facilitate the analysis of the CINDI-2 NO(2}) measurements. The model setup contains three nested domains with horizontal resolutions of 15, 3, and 1 km. Anthropogenic emissions are taken from the TNO-MACC III inventory and, where available, from the Dutch Pollutant Release and Transfer Register (Emissieregistratie), at a spatial resolution of 7 and 1 km, respectively. We use the Common Reactive Intermediates gas-phase chemical mechanism (CRIv2-R5) with the MOSAIC aerosol module. The high spatial resolution of model and emissions will allow us to resolve the strong spatial gradients in the NO(2) concentrations measured during the CINDI-2 campaign, allowing for an unprecedented level of detail in the analysis of individual pollution sources.

SimAlba: A Spatial Microsimulation Approach to the Analysis of Health Inequalities

PubMed Central

Campbell, Malcolm; Ballas, Dimitris

2016-01-01

This paper presents applied geographical research based on a spatial microsimulation model, SimAlba, aimed at estimating geographically sensitive health variables in Scotland. SimAlba has been developed in order to answer a variety of “what-if” policy questions pertaining to health policy in Scotland. Using the SimAlba model, it is possible to simulate the distributions of previously unknown variables at the small area level such as smoking, alcohol consumption, mental well-being, and obesity. The SimAlba microdataset has been created by combining Scottish Health Survey and Census data using a deterministic reweighting spatial microsimulation algorithm developed for this purpose. The paper presents SimAlba outputs for Scotland’s largest city, Glasgow, and examines the spatial distribution of the simulated variables for small geographical areas in Glasgow as well as the effects on individuals of different policy scenario outcomes. In simulating previously unknown spatial data, a wealth of new perspectives can be examined and explored. This paper explores a small set of those potential avenues of research and shows the power of spatial microsimulation modeling in an urban context. PMID:27818989

Study on temporal variation and spatial distribution for rural poverty in China based on GIS

NASA Astrophysics Data System (ADS)

Feng, Xianfeng; Xu, Xiuli; Wang, Yingjie; Cui, Jing; Mo, Hongyuan; Liu, Ling; Yan, Hong; Zhang, Yan; Han, Jiafu

2009-07-01

Poverty is one of the most serious challenges all over the world, is an obstacle to hinder economics and agriculture in poverty area. Research on poverty alleviation in China is very useful and important. In this paper, we will explore the comprehensive poverty characteristics in China, analyze the current poverty status, spatial distribution and temporal variations about rural poverty in China, and to category the different poverty types and their spatial distribution. First, we achieved the gathering and processing the relevant data. These data contain investigation data, research reports, statistical yearbook, censuses, social-economic data, physical and anthrop geographical data, etc. After deeply analysis of these data, we will get the distribution of poverty areas by spatial-temporal data model according to different poverty given standard in different stages in China to see the poverty variation and the regional difference in County-level. Then, the current poverty status, spatial pattern about poverty area in villages-level will be lucubrated; the relationship among poverty, environment (including physical and anthrop geographical factors) and economic development, etc. will be expanded. We hope our research will enhance the people knowledge of poverty in China and contribute to the poverty alleviation in China.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Model of Numerical Spatial Classification for Sustainable Agriculture in Badung Regency and Denpasar City, Indonesia

NASA Astrophysics Data System (ADS)

Trigunasih, N. M.; Lanya, I.; Subadiyasa, N. N.; Hutauruk, J.

2018-02-01

Increasing number and activity of the population to meet the needs of their lives greatly affect the utilization of land resources. Land needs for activities of the population continue to grow, while the availability of land is limited. Therefore, there will be changes in land use. As a result, the problems faced by land degradation and conversion of agricultural land become non-agricultural. The objectives of this research are: (1) to determine parameter of spatial numerical classification of sustainable food agriculture in Badung Regency and Denpasar City (2) to know the projection of food balance in Badung Regency and Denpasar City in 2020, 2030, 2040, and 2050 (3) to specify of function of spatial numerical classification in the making of zonation model of sustainable agricultural land area in Badung regency and Denpasar city (4) to determine the appropriate model of the area to protect sustainable agricultural land in spatial and time scale in Badung and Denpasar regencies. The method used in this research was quantitative method include: survey, soil analysis, spatial data development, geoprocessing analysis (spatial analysis of overlay and proximity analysis), interpolation of raster digital elevation model data, and visualization (cartography). Qualitative methods consisted of literature studies, and interviews. The parameters observed for a total of 11 parameters Badung regency and Denpasar as much as 9 parameters. Numerical classification parameter analysis results used the standard deviation and the mean of the population data and projections relationship rice field in the food balance sheet by modelling. The result of the research showed that, the number of different numerical classification parameters in rural areas (Badung) and urban areas (Denpasar), in urban areas the number of parameters is less than the rural areas. The based on numerical classification weighting and scores generate population distribution parameter analysis results of a standard deviation and average value. Numerical classification produced 5 models, which was divided into three zones are sustainable neighbourhood, buffer and converted in Denpasar and Badung. The results of Population curve parameter analysis in Denpasar showed normal curve, in contrast to the Badung regency showed abnormal curve, therefore Denpasar modeling carried out throughout the region, while in the Badung regency modeling done in each district. Relationship modelling and projections lands role in food balance in Badung views of sustainable land area whereas in Denpasar seen from any connection to the green open spaces in the spatial plan Denpasar 2011-2031. Modelling in Badung (rural) is different in Denpasar (urban), as well as population curve parameter analysis results in Badung showed abnormal curve while in Denpasar showed normal curve. Relationship modelling and projections lands role in food balance in the Badung regency sustainable in terms of land area, while in Denpasar in terms of linkages with urban green space in Denpasar City’s regional landuse plan of 2011-2031.

SPATIAL Short Courses Build Expertise and Community in Isotope Geochemistry

NASA Astrophysics Data System (ADS)

Riggs, E. M.; Bowen, G. J.

2015-12-01

The SPATIAL short course at the University of Utah is designed for graduate students and professionals in the earth and environmental sciences from around the globe. An integral part of the broader, NSF-funded Inter-university Training for Continental-scale Ecology (ITCE) project, the course is an intensive two-week field, classroom and laboratory experience with internationally-known researchers as instructors. The course focuses on stable isotope geochemistry coupled with spatial analysis techniques. Participants do not typically know each other or this research community well upon entering. One of the stated goals of the overall project is to build a community of practice around these techniques. This design is common in many professional fields, but is not often applied at the graduate level nor formally assessed in the earth sciences. Paired pre- and post-tests were administered before the start and after the close of the short courses over 3 years. The survey is a set of instruments adapted from social-cognitive psychology measuring changes in identity and community with other items to measure content knowledge outcomes. We see a subtle, consistent convergence of identities between large-scale isotope geochemistry and participants' research areas. Results also show that the course generates an increase in understanding about stable isotopes' use and application. The data show the SPATIAL course is very effective at bringing students together socially with each other and with faculty to create an environment that fosters community and scientific cooperation. Semi-structured pre-and post- interviews were conducted to understand the program elements that generated gains in learning and community. Participants were selected based on initial responses on the pre-survey to capture the range of initial conditions for the group. Qualitative analysis shows that the major factors for participants were 1) ready access to researchers in an informal setting during the course with many substantial opportunities to discuss research, 2) scaffolded, guided-inquiry group research designed to build group cohesion and skills, 3) just-in-time teaching at key junctures during lab and field exercises, and 4) access to curated sets of research literature from disparate fields relevant to SPATIAL content.

Affordances of Augmented Reality in Science Learning: Suggestions for Future Research

NASA Astrophysics Data System (ADS)

Cheng, Kun-Hung; Tsai, Chin-Chung

2013-08-01

Augmented reality (AR) is currently considered as having potential for pedagogical applications. However, in science education, research regarding AR-aided learning is in its infancy. To understand how AR could help science learning, this review paper firstly has identified two major approaches of utilizing AR technology in science education, which are named as image- based AR and location- based AR. These approaches may result in different affordances for science learning. It is then found that students' spatial ability, practical skills, and conceptual understanding are often afforded by image-based AR and location-based AR usually supports inquiry-based scientific activities. After examining what has been done in science learning with AR supports, several suggestions for future research are proposed. For example, more research is required to explore learning experience (e.g., motivation or cognitive load) and learner characteristics (e.g., spatial ability or perceived presence) involved in AR. Mixed methods of investigating learning process (e.g., a content analysis and a sequential analysis) and in-depth examination of user experience beyond usability (e.g., affective variables of esthetic pleasure or emotional fulfillment) should be considered. Combining image-based and location-based AR technology may bring new possibility for supporting science learning. Theories including mental models, spatial cognition, situated cognition, and social constructivist learning are suggested for the profitable uses of future AR research in science education.

Research into the influence of spatial variability and scale on the parameterization of hydrological processes

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1993-01-01

The objectives of the research were as follows: (1) Extend the Representative Elementary Area (RE) concept, first proposed and developed in Wood et al, (1988), to the water balance fluxes of the interstorm period (redistribution, evapotranspiration and baseflow) necessary for the analysis of long-term water balance processes. (2) Derive spatially averaged water balance model equations for spatially variable soil, topography and vegetation, over A RANGE OF CLIMATES. This is a necessary step in our goal to derive consistent hydrologic results up to GCM grid scales necessary for global climate modeling. (3) Apply the above macroscale water balance equations with remotely sensed data and begin to explore the feasibility of parameterizing the water balance constitutive equations at GCM grid scale.

A Comparative Analysis of Holographic, 3D-Printed, and Computer-Generated Models: Implications for Engineering Technology Students' Spatial Visualization Ability

ERIC Educational Resources Information Center

Katsioloudis, Petros J.; Jones, Mildred V.

2018-01-01

A number of studies indicate that the use of holographic displays can influence spatial visualization ability; however, research provides inconsistent results. Considering this, a quasi-experimental study was conducted to identify the existence of statistically significant effects on sectional view drawing ability due to the impacts of holographic…

Ted Kwasnik | NREL

Science.gov Websites

Architecture/Implementation of GIS Applications Open Source Programming and Web Development Spatial Analysis and Cartography Research Interests Transportation Systems and Urban Mobility Wind and Solar Resource

Memory processes of flight situation awareness: interactive roles of working memory capacity, long-term working memory, and expertise.

PubMed

Sohn, Young Woo; Doane, Stephanie M

2004-01-01

This research examined the role of working memory (WM) capacity and long-term working memory (LT-WM) in flight situation awareness (SA). We developed spatial and verbal measures of WM capacity and LT-WM skill and then determined the ability of these measures to predict pilot performance on SA tasks. Although both spatial measures of WM capacity and LT-WM skills were important predictors of SA performance, their importance varied as a function of pilot expertise. Spatial WM capacity was most predictive of SA performance for novices, whereas spatial LT-WM skill based on configurations of control flight elements (attitude and power) was most predictive for experts. Furthermore, evidence for an interactive role of WM and LT-WM mechanisms was indicated. Actual or potential applications of this research include cognitive analysis of pilot expertise and aviation training.

Spatial and temporal variance in fatty acid and stable isotope signatures across trophic levels in large river systems

USGS Publications Warehouse

Fritts, Andrea; Knights, Brent C.; Lafrancois, Toben D.; Bartsch, Lynn; Vallazza, Jon; Bartsch, Michelle; Richardson, William B.; Karns, Byron N.; Bailey, Sean; Kreiling, Rebecca

2018-01-01

Fatty acid and stable isotope signatures allow researchers to better understand food webs, food sources, and trophic relationships. Research in marine and lentic systems has indicated that the variance of these biomarkers can exhibit substantial differences across spatial and temporal scales, but this type of analysis has not been completed for large river systems. Our objectives were to evaluate variance structures for fatty acids and stable isotopes (i.e. δ13C and δ15N) of seston, threeridge mussels, hydropsychid caddisflies, gizzard shad, and bluegill across spatial scales (10s-100s km) in large rivers of the Upper Mississippi River Basin, USA that were sampled annually for two years, and to evaluate the implications of this variance on the design and interpretation of trophic studies. The highest variance for both isotopes was present at the largest spatial scale for all taxa (except seston δ15N) indicating that these isotopic signatures are responding to factors at a larger geographic level rather than being influenced by local-scale alterations. Conversely, the highest variance for fatty acids was present at the smallest spatial scale (i.e. among individuals) for all taxa except caddisflies, indicating that the physiological and metabolic processes that influence fatty acid profiles can differ substantially between individuals at a given site. Our results highlight the need to consider the spatial partitioning of variance during sample design and analysis, as some taxa may not be suitable to assess ecological questions at larger spatial scales.

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

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.

How spatial abilities and dynamic visualizations interplay when learning functional anatomy with 3D anatomical models.

PubMed

Berney, Sandra; Bétrancourt, Mireille; Molinari, Gaëlle; Hoyek, Nady

2015-01-01

The emergence of dynamic visualizations of three-dimensional (3D) models in anatomy curricula may be an adequate solution for spatial difficulties encountered with traditional static learning, as they provide direct visualization of change throughout the viewpoints. However, little research has explored the interplay between learning material presentation formats, spatial abilities, and anatomical tasks. First, to understand the cognitive challenges a novice learner would be faced with when first exposed to 3D anatomical content, a six-step cognitive task analysis was developed. Following this, an experimental study was conducted to explore how presentation formats (dynamic vs. static visualizations) support learning of functional anatomy, and affect subsequent anatomical tasks derived from the cognitive task analysis. A second aim was to investigate the interplay between spatial abilities (spatial visualization and spatial relation) and presentation formats when the functional anatomy of a 3D scapula and the associated shoulder flexion movement are learned. Findings showed no main effect of the presentation formats on performances, but revealed the predictive influence of spatial visualization and spatial relation abilities on performance. However, an interesting interaction between presentation formats and spatial relation ability for a specific anatomical task was found. This result highlighted the influence of presentation formats when spatial abilities are involved as well as the differentiated influence of spatial abilities on anatomical tasks. © 2015 American Association of Anatomists.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-08-01

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

SpatialEpiApp: A Shiny web application for the analysis of spatial and spatio-temporal disease data.

PubMed

Moraga, Paula

2017-11-01

During last years, public health surveillance has been facilitated by the existence of several packages implementing statistical methods for the analysis of spatial and spatio-temporal disease data. However, these methods are still inaccesible for many researchers lacking the adequate programming skills to effectively use the required software. In this paper we present SpatialEpiApp, a Shiny web application that integrate two of the most common approaches in health surveillance: disease mapping and detection of clusters. SpatialEpiApp is easy to use and does not require any programming knowledge. Given information about the cases, population and optionally covariates for each of the areas and dates of study, the application allows to fit Bayesian models to obtain disease risk estimates and their uncertainty by using R-INLA, and to detect disease clusters by using SaTScan. The application allows user interaction and the creation of interactive data visualizations and reports showing the analyses performed. Copyright © 2017 Elsevier Ltd. All rights reserved.

AITSO: A Tool for Spatial Optimization Based on Artificial Immune Systems

PubMed Central

Zhao, Xiang; Liu, Yaolin; Liu, Dianfeng; Ma, Xiaoya

2015-01-01

A great challenge facing geocomputation and spatial analysis is spatial optimization, given that it involves various high-dimensional, nonlinear, and complicated relationships. Many efforts have been made with regard to this specific issue, and the strong ability of artificial immune system algorithms has been proven in previous studies. However, user-friendly professional software is still unavailable, which is a great impediment to the popularity of artificial immune systems. This paper describes a free, universal tool, named AITSO, which is capable of solving various optimization problems. It provides a series of standard application programming interfaces (APIs) which can (1) assist researchers in the development of their own problem-specific application plugins to solve practical problems and (2) allow the implementation of some advanced immune operators into the platform to improve the performance of an algorithm. As an integrated, flexible, and convenient tool, AITSO contributes to knowledge sharing and practical problem solving. It is therefore believed that it will advance the development and popularity of spatial optimization in geocomputation and spatial analysis. PMID:25678911

Finding Food Deserts: A Comparison of Methods Measuring Spatial Access to Food Stores.

PubMed

Jaskiewicz, Lara; Block, Daniel; Chavez, Noel

2016-05-01

Public health research has increasingly focused on how access to resources affects health behaviors. Mapping environmental factors, such as distance to a supermarket, can identify intervention points toward improving food access in low-income and minority communities. However, the existing literature provides little guidance on choosing the most appropriate measures of spatial access. This study compared the results of different measures of spatial access to large food stores and the locations of high and low access identified by each. The data set included U.S. Census population data and the locations of large food stores in the six-county area around Chicago, Illinois. Six measures of spatial access were calculated at the census block group level and the results compared. The analysis found that there was little agreement in the identified locations of high or low access between measures. This study illustrates the importance of considering the access measure used when conducting research, interpreting results, or comparing studies. Future research should explore the correlation of different measures with health behaviors and health outcomes. © 2015 Society for Public Health Education.

Assessment of 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.

Mapping Vegetation Community Types in a Highly-Disturbed Landscape: Integrating Hiearchical Object-Based Image Analysis with Digital Surface Models

NASA Astrophysics Data System (ADS)

Snavely, Rachel A.

Focusing on the semi-arid and highly disturbed landscape of San Clemente Island, California, this research tests the effectiveness of incorporating a hierarchal object-based image analysis (OBIA) approach with high-spatial resolution imagery and light detection and range (LiDAR) derived canopy height surfaces for mapping vegetation communities. The study is part of a large-scale research effort conducted by researchers at San Diego State University's (SDSU) Center for Earth Systems Analysis Research (CESAR) and Soil Ecology and Restoration Group (SERG), to develop an updated vegetation community map which will support both conservation and management decisions on Naval Auxiliary Landing Field (NALF) San Clemente Island. Trimble's eCognition Developer software was used to develop and generate vegetation community maps for two study sites, with and without vegetation height data as input. Overall and class-specific accuracies were calculated and compared across the two classifications. The highest overall accuracy (approximately 80%) was observed with the classification integrating airborne visible and near infrared imagery having very high spatial resolution with a LiDAR derived canopy height model. Accuracies for individual vegetation classes differed between both classification methods, but were highest when incorporating the LiDAR digital surface data. The addition of a canopy height model, however, yielded little difference in classification accuracies for areas of very dense shrub cover. Overall, the results show the utility of the OBIA approach for mapping vegetation with high spatial resolution imagery, and emphasizes the advantage of both multi-scale analysis and digital surface data for accuracy characterizing highly disturbed landscapes. The integrated imagery and digital canopy height model approach presented both advantages and limitations, which have to be considered prior to its operational use in mapping vegetation communities.

Earth Observation, Spatial Data Quality, and Neglected Tropical Diseases.

PubMed

Hamm, Nicholas A S; Soares Magalhães, Ricardo J; Clements, Archie C A

2015-12-01

Earth observation (EO) is the use of remote sensing and in situ observations to gather data on the environment. It finds increasing application in the study of environmentally modulated neglected tropical diseases (NTDs). Obtaining and assuring the quality of the relevant spatially and temporally indexed EO data remain challenges. Our objective was to review the Earth observation products currently used in studies of NTD epidemiology and to discuss fundamental issues relating to spatial data quality (SDQ), which limit the utilization of EO and pose challenges for its more effective use. We searched Web of Science and PubMed for studies related to EO and echinococossis, leptospirosis, schistosomiasis, and soil-transmitted helminth infections. Relevant literature was also identified from the bibliographies of those papers. We found that extensive use is made of EO products in the study of NTD epidemiology; however, the quality of these products is usually given little explicit attention. We review key issues in SDQ concerning spatial and temporal scale, uncertainty, and the documentation and use of quality information. We give examples of how these issues may interact with uncertainty in NTD data to affect the output of an epidemiological analysis. We conclude that researchers should give careful attention to SDQ when designing NTD spatial-epidemiological studies. This should be used to inform uncertainty analysis in the epidemiological study. SDQ should be documented and made available to other researchers.

Quantitative analysis of spatial variability of geotechnical parameters

NASA Astrophysics Data System (ADS)

Fang, Xing

2018-04-01

Geotechnical parameters are the basic parameters of geotechnical engineering design, while the geotechnical parameters have strong regional characteristics. At the same time, the spatial variability of geotechnical parameters has been recognized. It is gradually introduced into the reliability analysis of geotechnical engineering. Based on the statistical theory of geostatistical spatial information, the spatial variability of geotechnical parameters is quantitatively analyzed. At the same time, the evaluation of geotechnical parameters and the correlation coefficient between geotechnical parameters are calculated. A residential district of Tianjin Survey Institute was selected as the research object. There are 68 boreholes in this area and 9 layers of mechanical stratification. The parameters are water content, natural gravity, void ratio, liquid limit, plasticity index, liquidity index, compressibility coefficient, compressive modulus, internal friction angle, cohesion and SP index. According to the principle of statistical correlation, the correlation coefficient of geotechnical parameters is calculated. According to the correlation coefficient, the law of geotechnical parameters is obtained.

Gis-Based Accessibility Analysis of Urban Emergency Shelters: the Case of Adana City

NASA Astrophysics Data System (ADS)

Unal, M.; Uslu, C.

2016-10-01

Accessibility analysis of urban emergency shelters can help support urban disaster prevention planning. Pre-disaster emergency evacuation zoning has become a significant topic on disaster prevention and mitigation research. In this study, we assessed the level of serviceability of urban emergency shelters within maximum capacity, usability, sufficiency and a certain walking time limit by employing spatial analysis techniques of GIS-Network Analyst. The methodology included the following aspects: the distribution analysis of emergency evacuation demands, the calculation of shelter space accessibility and the optimization of evacuation destinations. This methodology was applied to Adana, a city in Turkey, which is located within the Alpine-Himalayan orogenic system, the second major earthquake belt after the Pacific-Belt. It was found that the proposed methodology could be useful in aiding to understand the spatial distribution of urban emergency shelters more accurately and establish effective future urban disaster prevention planning. Additionally, this research provided a feasible way for supporting emergency management in terms of shelter construction, pre-disaster evacuation drills and rescue operations.

Depth data research of GIS based on clustering analysis algorithm

NASA Astrophysics Data System (ADS)

Xiong, Yan; Xu, Wenli

2018-03-01

The data of GIS have spatial distribution. Geographic data has both spatial characteristics and attribute characteristics, and also changes with time. Therefore, the amount of data is very large. Nowadays, many industries and departments in the society are using GIS. However, without proper data analysis and mining scheme, GIS will not exert its maximum effectiveness and will waste a lot of data. In this paper, we use the geographic information demand of a national security department as the experimental object, combining the characteristics of GIS data, taking into account the characteristics of time, space, attributes and so on, and using cluster analysis algorithm. We further study the mining scheme for depth data, and get the algorithm model. This algorithm can automatically classify sample data, and then carry out exploratory analysis. The research shows that the algorithm model and the information mining scheme can quickly find hidden depth information from the surface data of GIS, thus improving the efficiency of the security department. This algorithm can also be extended to other fields.

Effectiveness of Drafting Models for Engineering Technology Students and Impacts on Spatial Visualization Ability: An Analysis and Consideration of Critical Variables

ERIC Educational Resources Information Center

Katsioloudis, Petros J.; Stefaniak, Jill E.

2018-01-01

Results from a number of studies indicate that the use of drafting models can positively influence the spatial visualization ability for engineering technology students. However, additional variables such as light, temperature, motion and color can play an important role but research provides inconsistent results. Considering this, a set of 5…

Trace Analysis and Spatial Reasoning: An Example of Intensive Cognitive Diagnosis and Its Implications for Testing.

DTIC Science & Technology

1987-09-01

of Intensive Cognitive Diagnosis and Its Implications for Testing Stellan Ohisson Learning Research and Development Center, University of Pittsburgh...7a. NAME OF MONITORING ORGANIZATION Learning Research & Development (if applicable) Cognitive Science Program Center, University of Pittsburg Office of...GAGE All other eaitions are obolSete. UN CLASS " UNLASSI FIED Ohlsson 1 Trace Analysis Knowledge and Understanding in Human Learning Knowledge and

Geographic Information Systems and Martian Data: Compatibility and Analysis

NASA Technical Reports Server (NTRS)

Jones, Jennifer L.

2005-01-01

Planning future landed Mars missions depends on accurate, informed data. This research has created and used spatially referenced instrument data from NASA missions such as the Thermal Emission Imaging System (THEMIS) on the Mars Odyssey Orbiter and the Mars Orbital Camera (MOC) on the Mars Global Surveyor (MGS) Orbiter. Creating spatially referenced data enables its use in Geographic Information Systems (GIS) such as ArcGIS. It has then been possible to integrate this spatially referenced data with global base maps and build and populate location based databases that are easy to access.

A look at spatial abilities in undergraduate women science majors

NASA Astrophysics Data System (ADS)

Lord, Thomas R.

Contemporary investigations indicate that men generally perform significantly better in tasks involving visuo-spatial awareness than do women. Researchers have attempted to explain this difference through several hypotheses but as yet the reason for the dimorphism has not been established. Further, contemporary studies have indicated that enhancement of mental image formation and manipulation is possible when students are subjected to carefully designed spatial interventions. Present research was conducted to see if women in the sciences were as spatial perceptively accurate as their male counterparts. The researcher also was interested to find if the women that received the intervention excercises improved in their visuo-spatial awareness as rapidly as their male counterparts.The study was conducted on science majors at a suburban two year college. The population was randomly divided into groups (experimental, placebo, and control) each containing approximately the same number of men and women. All groups were given a battery of spatial perception tests (Ekstrom et al, 1976) at the onset of the winter semester and a second version of the battery at the conclusion of the semester. An analysis of variance followed by Scheffe contrasts were run on the results. The statistics revealed that the experimental group significantly outperformed the nonexperimental groups on the tests. When the differences between the mean scores for the women in the experimental group were statistically compared to those of the men in the experimental group the women were improving at a more rapid rate. Many women have the capacity to develop visuo-spatial aptitude and although they may start out behind men in spatial ability, they learn quickly and often catch up to the men's level when given meaningful visuo-spatial interventions.

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia.

PubMed

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-06-27

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America.

A Development of Nonstationary Regional Frequency Analysis Model with Large-scale Climate Information: Its Application to Korean Watershed

NASA Astrophysics Data System (ADS)

Kim, Jin-Young; Kwon, Hyun-Han; Kim, Hung-Soo

2015-04-01

The existing regional frequency analysis has disadvantages in that it is difficult to consider geographical characteristics in estimating areal rainfall. In this regard, this study aims to develop a hierarchical Bayesian model based nonstationary regional frequency analysis in that spatial patterns of the design rainfall with geographical information (e.g. latitude, longitude and altitude) are explicitly incorporated. This study assumes that the parameters of Gumbel (or GEV distribution) are a function of geographical characteristics within a general linear regression framework. Posterior distribution of the regression parameters are estimated by Bayesian Markov Chain Monte Carlo (MCMC) method, and the identified functional relationship is used to spatially interpolate the parameters of the distributions by using digital elevation models (DEM) as inputs. The proposed model is applied to derive design rainfalls over the entire Han-river watershed. It was found that the proposed Bayesian regional frequency analysis model showed similar results compared to L-moment based regional frequency analysis. In addition, the model showed an advantage in terms of quantifying uncertainty of the design rainfall and estimating the area rainfall considering geographical information. Finally, comprehensive discussion on design rainfall in the context of nonstationary will be presented. KEYWORDS: Regional frequency analysis, Nonstationary, Spatial information, Bayesian Acknowledgement This research was supported by a grant (14AWMP-B082564-01) from Advanced Water Management Research Program funded by Ministry of Land, Infrastructure and Transport of Korean government.

Network-based spatial clustering technique for exploring features in regional industry

NASA Astrophysics Data System (ADS)

Chou, Tien-Yin; Huang, Pi-Hui; Yang, Lung-Shih; Lin, Wen-Tzu

2008-10-01

In the past researches, industrial cluster mainly focused on single or particular industry and less on spatial industrial structure and mutual relations. Industrial cluster could generate three kinds of spillover effects, including knowledge, labor market pooling, and input sharing. In addition, industrial cluster indeed benefits industry development. To fully control the status and characteristics of district industrial cluster can facilitate to improve the competitive ascendancy of district industry. The related researches on industrial spatial cluster were of great significance for setting up industrial policies and promoting district economic development. In this study, an improved model, GeoSOM, that combines DBSCAN (Density-Based Spatial Clustering of Applications with Noise) and SOM (Self-Organizing Map) was developed for analyzing industrial cluster. Different from former distance-based algorithm for industrial cluster, the proposed GeoSOM model can calculate spatial characteristics between firms based on DBSCAN algorithm and evaluate the similarity between firms based on SOM clustering analysis. The demonstrative data sets, the manufacturers around Taichung County in Taiwan, were analyzed for verifying the practicability of the proposed model. The analyzed results indicate that GeoSOM is suitable for evaluating spatial industrial cluster.

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

DOE PAGES

Belianinov, Alex; Panchapakesan, G.; Lin, Wenzhi; ...

2014-12-02

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe0.55Se0.45 (Tc = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe1 x Sex structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified by their electronic signaturemore » and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.« less

Research Update: Spatially resolved mapping of electronic structure on atomic level by multivariate statistical analysis

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

Belianinov, Alex, E-mail: belianinova@ornl.gov; Ganesh, Panchapakesan; Lin, Wenzhi

2014-12-01

Atomic level spatial variability of electronic structure in Fe-based superconductor FeTe{sub 0.55}Se{sub 0.45} (T{sub c} = 15 K) is explored using current-imaging tunneling-spectroscopy. Multivariate statistical analysis of the data differentiates regions of dissimilar electronic behavior that can be identified with the segregation of chalcogen atoms, as well as boundaries between terminations and near neighbor interactions. Subsequent clustering analysis allows identification of the spatial localization of these dissimilar regions. Similar statistical analysis of modeled calculated density of states of chemically inhomogeneous FeTe{sub 1−x}Se{sub x} structures further confirms that the two types of chalcogens, i.e., Te and Se, can be identified bymore » their electronic signature and differentiated by their local chemical environment. This approach allows detailed chemical discrimination of the scanning tunneling microscopy data including separation of atomic identities, proximity, and local configuration effects and can be universally applicable to chemically and electronically inhomogeneous surfaces.« less

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

PubMed

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

2004-11-01

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

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.

Remote sensing information sciences research group

NASA Technical Reports Server (NTRS)

Estes, John E.; Smith, Terence; Star, Jeffrey L.

1988-01-01

Research conducted under this grant was used to extend and expand existing remote sensing activities at the University of California, Santa Barbara in the areas of georeferenced information systems, matching assisted information extraction from image data and large spatial data bases, artificial intelligence, and vegetation analysis and modeling. The research thrusts during the past year are summarized. The projects are discussed in some detail.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Demand-supply dynamics in tourism systems: A spatio-temporal GIS analysis. The Alberta ski industry case study

NASA Astrophysics Data System (ADS)

Bertazzon, Stefania

The present research focuses on the interaction of supply and demand of down-hill ski tourism in the province of Alberta. The main hypothesis is that the demand for skiing depends on the socio-economic and demographic characteristics of the population living in the province and outside it. A second, consequent hypothesis is that the development of ski resorts (supply) is a response to the demand for skiing. From the latter derives the hypothesis of a dynamic interaction between supply (ski resorts) and demand (skiers). Such interaction occurs in space, within a range determined by physical distance and the means available to overcome it. The above hypotheses implicitly define interactions that take place in space and evolve over time. The hypotheses are tested by temporal, spatial, and spatio-temporal regression models, using the best available data and the latest commercially available software. The main purpose of this research is to explore analytical techniques to model spatial, temporal, and spatio-temporal dynamics in the context of regional science. The completion of the present research has produced more significant contributions than was originally expected. Many of the unexpected contributions resulted from theoretical and applied needs arising from the application of spatial regression models. Spatial regression models are a new and largely under-applied technique. The models are fairly complex and a considerable amount of preparatory work is needed, prior to their specification and estimation. Most of this work is specific to the field of application. The originality of the solutions devised is increased by the lack of applications in the field of tourism. The scarcity of applications in other fields adds to their value for other applications. The estimation of spatio-temporal models has been only partially attained in the present research. This apparent limitation is due to the novelty and complexity of the analytical methods applied. This opens new directions for further work in the field of spatial analysis, in conjunction with the development of specific software.

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

NASA Technical Reports Server (NTRS)

Heydorn, R. D.

1984-01-01

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

Spatial Hearing, Attention and Informational Masking in Speech Identification

DTIC Science & Technology

2012-09-12

Midwinter Research Meeting of the Association for Research in Otolaryngology, and at the annual Binaural Bash conference held at Boston University...rather than traditional binaural analysis mechanisms (also related see Best et al., 2005; Allen et al., 2008). The term " binaural analysis" is often...used as a catch-all for any binaural advantage that is not a consequence of simple acoustics (i.e., differential attenuation of sounds at the two

Spatiotemporal Data Mining, Analysis, and Visualization of Human Activity Data

ERIC Educational Resources Information Center

Li, Xun

2012-01-01

This dissertation addresses the research challenge of developing efficient new methods for discovering useful patterns and knowledge in large volumes of electronically collected spatiotemporal activity data. I propose to analyze three types of such spatiotemporal activity data in a methodological framework that integrates spatial analysis, data…

Use and misuse of landscape indices

Treesearch

Harbin Li; Jianguo Wu

2004-01-01

Landscape ecology has generated much excitement in the past two decades. One reason was that it brought spatial analysis and modeling to the forefront of ecological research. However, high expectations for landscape analysis to improve our understanding and prediction of ecological processes have largely been unfulfilled. We identified three kinds of critical issues:...

Research on golden-winged warblers: recent progress and current needs

Treesearch

Henry M. Streby; Ronald W. Rohrbaugh; David A. Buehler; David E. Andersen; Rachel Vallender; David I. King; Tom Will

2016-01-01

Considerable advances have been made in knowledge about Golden-winged Warblers (Vermivora chrysoptera) in the past decade. Recent employment of molecular analysis, stable-isotope analysis, telemetry-based monitoring of survival and behavior, and spatially explicit modeling techniques have added to, and revised, an already broad base of published...

Influence of pedestrian age and gender on spatial and temporal distribution of pedestrian crashes.

PubMed

Toran Pour, Alireza; Moridpour, Sara; Tay, Richard; Rajabifard, Abbas

2018-01-02

Every year, about 1.24 million people are killed in traffic crashes worldwide and more than 22% of these deaths are pedestrians. Therefore, pedestrian safety has become a significant traffic safety issue worldwide. In order to develop effective and targeted safety programs, the location- and time-specific influences on vehicle-pedestrian crashes must be assessed. The main purpose of this research is to explore the influence of pedestrian age and gender on the temporal and spatial distribution of vehicle-pedestrian crashes to identify the hotspots and hot times. Data for all vehicle-pedestrian crashes on public roadways in the Melbourne metropolitan area from 2004 to 2013 are used in this research. Spatial autocorrelation is applied in examining the vehicle-pedestrian crashes in geographic information systems (GIS) to identify any dependency between time and location of these crashes. Spider plots and kernel density estimation (KDE) are then used to determine the temporal and spatial patterns of vehicle-pedestrian crashes for different age groups and genders. Temporal analysis shows that pedestrian age has a significant influence on the temporal distribution of vehicle-pedestrian crashes. Furthermore, men and women have different crash patterns. In addition, results of the spatial analysis shows that areas with high risk of vehicle-pedestrian crashes can vary during different times of the day for different age groups and genders. For example, for those between ages 18 and 65, most vehicle-pedestrian crashes occur in the central business district (CBD) during the day, but between 7:00 p.m. and 6:00 a.m., crashes among this age group occur mostly around hotels, clubs, and bars. This research reveals that temporal and spatial distributions of vehicle-pedestrian crashes vary for different pedestrian age groups and genders. Therefore, specific safety measures should be in place during high crash times at different locations for different age groups and genders to increase the effectiveness of the countermeasures in preventing and reducing vehicle-pedestrian crashes.

Human factor design of habitable space facilities

NASA Technical Reports Server (NTRS)

Clearwater, Yvonne A.

1987-01-01

Current fundamental and applied habitability research conducted as part of the U.S. space program is reviewed with emphasis on methods, findings, and applications of the results to the planning and design of the International Space Station. The discussion covers the following six concurrent directions of habitability research: operational simulation, functional interior decor research, space crew privacy requirements, interior layout and configuration analysis, human spatial habitability model, and analogous environments research.

Spatial and Climate Literacy: Connecting Urban and Rural Students

NASA Astrophysics Data System (ADS)

Boger, R. A.; Low, R.; Mandryk, C.; Gorokhovich, Y.

2013-12-01

Through a collaboration between the University of Nebraska-Lincoln (UNL), Brooklyn College, and Lehman College, four independent but linked modules were developed and piloted in courses offered at Brooklyn College and UNL simultaneously. Module content includes climate change science and literacy principles, using geospatial technologies (GIS, GPS and remote sensing) as a vehicle to explore issues associated with global, regional, and local climate change in a concrete, quantitative and visual way using Internet resources available through NASA, NOAA, USGS, and a variety of universities and organizations. The materials take an Earth system approach and incorporate sustainability, resilience, water and watersheds, weather and climate, and food security topics throughout the semester. The research component of the project focuses on understanding the role of spatial literacy and authentic inquiry based experiences in climate change understanding and improving confidence in teaching science. In particular, engaging learners in both climate change science and GIS simultaneously provides opportunities to examine questions about the role that data manipulation, mental representation, and spatial literacy plays in students' abilities to understand the consequences and impacts of climate change. Pre and post surveys were designed to discern relationships between spatial cognitive processes and effective acquisition of climate change science concepts in virtual learning environments as well as alignment of teacher's mental models of nature of science and climate system dynamics to scientific models. The courses will again be offered simultaneously in Spring 2014 at Brooklyn College and UNL. Evaluation research will continue to examine the connections between spatial and climate literacy and teacher's mental models (via qualitative textual analysis using MAXQDA text analysis, and UCINET social network analysis programs) as well as how urban-rural learning interactions may influence climate literacy.

Does context matter for the relationship between deprivation and all-cause mortality? The West vs. the rest of Scotland

PubMed Central

2011-01-01

Background A growing body of research emphasizes the importance of contextual factors on health outcomes. Using postcode sector data for Scotland (UK), this study tests the hypothesis of spatial heterogeneity in the relationship between area-level deprivation and mortality to determine if contextual differences in the West vs. the rest of Scotland influence this relationship. Research into health inequalities frequently fails to recognise spatial heterogeneity in the deprivation-health relationship, assuming that global relationships apply uniformly across geographical areas. In this study, exploratory spatial data analysis methods are used to assess local patterns in deprivation and mortality. Spatial regression models are then implemented to examine the relationship between deprivation and mortality more formally. Results The initial exploratory spatial data analysis reveals concentrations of high standardized mortality ratios (SMR) and deprivation (hotspots) in the West of Scotland and concentrations of low values (coldspots) for both variables in the rest of the country. The main spatial regression result is that deprivation is the only variable that is highly significantly correlated with all-cause mortality in all models. However, in contrast to the expected spatial heterogeneity in the deprivation-mortality relationship, this relation does not vary between regions in any of the models. This result is robust to a number of specifications, including weighting for population size, controlling for spatial autocorrelation and heteroskedasticity, assuming a non-linear relationship between mortality and socio-economic deprivation, separating the dependent variable into male and female SMRs, and distinguishing between West, North and Southeast regions. The rejection of the hypothesis of spatial heterogeneity in the relationship between socio-economic deprivation and mortality complements prior research on the stability of the deprivation-mortality relationship over time. Conclusions The homogeneity we found in the deprivation-mortality relationship across the regions of Scotland and the absence of a contextualized effect of region highlights the importance of taking a broader strategic policy that can combat the toxic impacts of socio-economic deprivation on health. Focusing on a few specific places (e.g. 15% of the poorest areas) to concentrate resources might be a good start but the impact of socio-economic deprivation on mortality is not restricted to a few places. A comprehensive strategy that can be sustained over time might be needed to interrupt the linkages between poverty and mortality. PMID:21569408

Application of spatial Poisson process models to air mass thunderstorm rainfall

NASA Technical Reports Server (NTRS)

Eagleson, P. S.; Fennessy, N. M.; Wang, Qinliang; Rodriguez-Iturbe, I.

1987-01-01

Eight years of summer storm rainfall observations from 93 stations in and around the 154 sq km Walnut Gulch catchment of the Agricultural Research Service, U.S. Department of Agriculture, in Arizona are processed to yield the total station depths of 428 storms. Statistical analysis of these random fields yields the first two moments, the spatial correlation and variance functions, and the spatial distribution of total rainfall for each storm. The absolute and relative worth of three Poisson models are evaluated by comparing their prediction of the spatial distribution of storm rainfall with observations from the second half of the sample. The effect of interstorm parameter variation is examined.

Social Capital and Human Mortality: Explaining the Rural Paradox with County-Level Mortality Data

PubMed Central

Jensen, Leif; Haran, Murali

2014-01-01

The “rural paradox” refers to standardized mortality rates in rural areas that are unexpectedly low in view of well-known economic and infrastructural disadvantages there. We explore this paradox by incorporating social capital, a promising explanatory factor that has seldom been incorporated into residential mortality research. We do so while being attentive to spatial dependence, a statistical problem often ignored in mortality research. Analyzing data for counties in the contiguous United States, we find that: (1) the rural paradox is confirmed with both metro/non-metro and rural-urban continuum codes, (2) social capital significantly reduces the impacts of residence on mortality after controlling for race/ethnicity and socioeconomic covariates, (3) this attenuation is greater when a spatial perspective is imposed on the analysis, (4) social capital is negatively associated with mortality at the county level, and (5) spatial dependence is strongly in evidence. A spatial approach is necessary in county-level analyses such as ours to yield unbiased estimates and optimal model fit. PMID:25392565

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

Spatial Econometric Research on the Relationship between Highway Construction and Regional Economic Growth in China: Evidence from the Nationwide Panel Data

NASA Astrophysics Data System (ADS)

Ye, N. J.; Li, W. J.; Li, Y.; Bai, Y. F.

2017-12-01

Based on spatial panel data from 2010 to 2016 in China, this paper makes an empirical analysis on the relationship between highway construction and regional economic growth by means of spatial econometric model. The results show that there is positive spatial correlation on regional economic growth in China, and strong spatial dependences between some provinces and cities appear, specifically, Hebei, Beijing, Tianjin, Shanghai, Zhejiang and other eastern coastal areas show high-high agglomeration trend, the Pearl River Delta region presents high-low agglomeration trend; In terms of nationwide provinces and municipalities, a province’s highway construction investment for their own province and the neighboring provinces has pulling effect on economic growth to a certain extent, and the direct effect is more obvious.

Research on the key technology of update of land survey spatial data based on embedded GIS and GPS

NASA Astrophysics Data System (ADS)

Chen, Dan; Liu, Yanfang; Yu, Hai; Xia, Yin

2009-10-01

According to the actual needs of the second land-use survey and the PDA's characteristics of small volume and small memory, it can be analyzed that the key technology of the data collection system of field survey based on GPS-PDA is the read speed of the data. In order to enhance the speed and efficiency of the analysis of the spatial data on mobile devices, we classify the layers of spatial data; get the Layer-Grid Index by getting the different levels and blocks of the layer of spatial data; then get the R-TREE index of the spatial data objects. Different scale levels of space are used in different levels management. The grid method is used to do the block management.

Meet EPA Scientist Betsy Smith, Ph.D.

EPA Pesticide Factsheets

Dr. Betsy Smith is Associate National Program Director for Systems Analysis within the Sustainable and Healthy Communities Research Program. Her work has focused on new methods to analyze spatial data on multiple problems.

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

NASA Astrophysics Data System (ADS)

Fauzi, A. F.; Aditianata, A.

2018-02-01

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

Geospatial and machine learning techniques for wicked social science problems: analysis of crash severity on a regional highway corridor

NASA Astrophysics Data System (ADS)

Effati, Meysam; Thill, Jean-Claude; Shabani, Shahin

2015-04-01

The contention of this paper is that many social science research problems are too "wicked" to be suitably studied using conventional statistical and regression-based methods of data analysis. This paper argues that an integrated geospatial approach based on methods of machine learning is well suited to this purpose. Recognizing the intrinsic wickedness of traffic safety issues, such approach is used to unravel the complexity of traffic crash severity on highway corridors as an example of such problems. The support vector machine (SVM) and coactive neuro-fuzzy inference system (CANFIS) algorithms are tested as inferential engines to predict crash severity and uncover spatial and non-spatial factors that systematically relate to crash severity, while a sensitivity analysis is conducted to determine the relative influence of crash severity factors. Different specifications of the two methods are implemented, trained, and evaluated against crash events recorded over a 4-year period on a regional highway corridor in Northern Iran. Overall, the SVM model outperforms CANFIS by a notable margin. The combined use of spatial analysis and artificial intelligence is effective at identifying leading factors of crash severity, while explicitly accounting for spatial dependence and spatial heterogeneity effects. Thanks to the demonstrated effectiveness of a sensitivity analysis, this approach produces comprehensive results that are consistent with existing traffic safety theories and supports the prioritization of effective safety measures that are geographically targeted and behaviorally sound on regional highway corridors.

Detecting spatial regimes in ecosystems | Science Inventory ...

EPA Pesticide Factsheets

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory based method, on both terrestrial and aquatic animal data (US Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps, and multivariate analysis such as nMDS (non-metric Multidimensional Scaling) and cluster analysis. We successfully detect spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change. Use an information theory based method to identify ecological boundaries and compare our results to traditional early warning

Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination

PubMed Central

Ha, Hoehun; Rogerson, Peter A.; Olson, James R.; Han, Daikwon; Bian, Ling; Shao, Wanyun

2016-01-01

Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations. PMID:27649221

Analysis of Pollution Hazard Intensity: A Spatial Epidemiology Case Study of Soil Pb Contamination.

PubMed

Ha, Hoehun; Rogerson, Peter A; Olson, James R; Han, Daikwon; Bian, Ling; Shao, Wanyun

2016-09-14

Heavy industrialization has resulted in the contamination of soil by metals from anthropogenic sources in Anniston, Alabama. This situation calls for increased public awareness of the soil contamination issue and better knowledge of the main factors contributing to the potential sources contaminating residential soil. The purpose of this spatial epidemiology research is to describe the effects of physical factors on the concentration of lead (Pb) in soil in Anniston AL, and to determine the socioeconomic and demographic characteristics of those residing in areas with higher soil contamination. Spatial regression models are used to account for spatial dependencies using these explanatory variables. After accounting for covariates and multicollinearity, results of the analysis indicate that lead concentration in soils varies markedly in the vicinity of a specific foundry (Foundry A), and that proximity to railroads explained a significant amount of spatial variation in soil lead concentration. Moreover, elevated soil lead levels were identified as a concern in industrial sites, neighborhoods with a high density of old housing, a high percentage of African American population, and a low percent of occupied housing units. The use of spatial modelling allows for better identification of significant factors that are correlated with soil lead concentrations.

Superfund, Hedonics, and the Scales of Environmental Justice

NASA Astrophysics Data System (ADS)

Noonan, Douglas S.; Turaga, Rama Mohana R.; Baden, Brett M.

2009-11-01

Environmental justice (EJ) is prominent in environmental policy, yet EJ research is plagued by debates over methodological procedures. A well-established economic approach, the hedonic price method, can offer guidance on one contentious aspect of EJ research: the choice of the spatial unit of analysis. Environmental managers charged with preventing or remedying inequities grapple with these framing problems. This article reviews the theoretical and empirical literature on unit choice in EJ, as well as research employing hedonic pricing to assess the spatial extent of hazardous waste site impacts. The insights from hedonics are demonstrated in a series of EJ analyses for a national inventory of Superfund sites. First, as evidence of injustice exhibits substantial sensitivity to the choice of spatial unit, hedonics suggests some units conform better to Superfund impacts than others. Second, hedonic estimates for a particular site can inform the design of appropriate tests of environmental inequity for that site. Implications for policymakers and practitioners of EJ analyses are discussed.

Superfund, hedonics, and the scales of environmental justice.

PubMed

Noonan, Douglas S; Turaga, Rama Mohana R; Baden, Brett M

2009-11-01

Environmental justice (EJ) is prominent in environmental policy, yet EJ research is plagued by debates over methodological procedures. A well-established economic approach, the hedonic price method, can offer guidance on one contentious aspect of EJ research: the choice of the spatial unit of analysis. Environmental managers charged with preventing or remedying inequities grapple with these framing problems. This article reviews the theoretical and empirical literature on unit choice in EJ, as well as research employing hedonic pricing to assess the spatial extent of hazardous waste site impacts. The insights from hedonics are demonstrated in a series of EJ analyses for a national inventory of Superfund sites. First, as evidence of injustice exhibits substantial sensitivity to the choice of spatial unit, hedonics suggests some units conform better to Superfund impacts than others. Second, hedonic estimates for a particular site can inform the design of appropriate tests of environmental inequity for that site. Implications for policymakers and practitioners of EJ analyses are discussed.

Composition/Structure/Dynamics of comet and planetary satellite atmospheres

NASA Technical Reports Server (NTRS)

Combi, Michael R. (Principal Investigator)

1995-01-01

This research program addresses two cases of tenuous planetary atmospheres: comets and Io. The comet atmospheric research seeks to analyze a set of spatial profiles of CN in comet Halley taken in a 7.4-day period in April 1986; to apply a new dust coma model to various observations; and to analyze observations of the inner hydrogen coma, which can be optically thick to the resonance scattering of Lyman-alpha radiation, with the newly developed approach that combines a spherical radiative transfer model with our Monte Carlo H coma model. The Io research seeks to understand the atmospheric escape from Io with a hybrid-kinetic model for neutral gases and plasma given methods and algorithms developed for the study of neutral gas cometary atmospheres and the earth's polar wind and plasmasphere. Progress is reported on cometary Hydrogen Lyman-alpha studies; time-series analysis of cometary spatial profiles; model analysis of the dust comae of comets; and a global kinetic atmospheric model of Io.

Spatial Analysis of Land Subsidence and Flood Pattern Based on DInSAR Method in Sentinel Sar Imagery and Weighting Method in Geo-Hazard Parameters Combination in North Jakarta Region

NASA Astrophysics Data System (ADS)

Prasetyo, Y.; Yuwono, B. D.; Ramadhanis, Z.

2018-02-01

The reclamation program carried out in most cities in North Jakarta is directly adjacent to the Jakarta Bay. Beside this program, the density of population and development center in North Jakarta office has increased the need for underground water excessively. As a result of these things, land subsidence in North Jakarta area is relatively high and so intense. The research methodology was developed based on the method of remote sensing and geographic information systems, expected to describe the spatial correlation between the land subsidence and flood phenomenon in North Jakarta. The DInSAR (Differential Interferometric Synthetic Aperture Radar) method with satellite image data Radar (SAR Sentinel 1A) for the years 2015 to 2016 acquisitions was used in this research. It is intended to obtain a pattern of land subsidence in North Jakarta and then combined with flood patterns. For the preparation of flood threat zoning pattern, this research has been modeling in spatial technique based on a weighted parameter of rainfall, elevation, flood zones and land use. In the final result, we have obtained a flood hazard zonation models then do the overlap against DInSAR processing results. As a result of the research, Geo-hazard modelling has a variety results as: 81% of flood threat zones consist of rural area, 12% consists of un-built areas and 7% consists of water areas. Furthermore, the correlation of land subsidence to flood risk zone is divided into three levels of suitability with 74% in high class, 22% in medium class and 4% in low class. For the result of spatial correlation area between land subsidence and flood risk zone are 77% detected in rural area, 17% detected in un-built area and 6% detected in a water area. Whereas the research product is the geo-hazard maps in North Jakarta as the basis of the spatial correlation analysis between the land subsidence and flooding phenomena.double point.

Hyperspectral Image Denoising Using a Nonlocal Spectral Spatial Principal Component Analysis

NASA Astrophysics Data System (ADS)

Li, D.; Xu, L.; Peng, J.; Ma, J.

2018-04-01

Hyperspectral images (HSIs) denoising is a critical research area in image processing duo to its importance in improving the quality of HSIs, which has a negative impact on object detection and classification and so on. In this paper, we develop a noise reduction method based on principal component analysis (PCA) for hyperspectral imagery, which is dependent on the assumption that the noise can be removed by selecting the leading principal components. The main contribution of paper is to introduce the spectral spatial structure and nonlocal similarity of the HSIs into the PCA denoising model. PCA with spectral spatial structure can exploit spectral correlation and spatial correlation of HSI by using 3D blocks instead of 2D patches. Nonlocal similarity means the similarity between the referenced pixel and other pixels in nonlocal area, where Mahalanobis distance algorithm is used to estimate the spatial spectral similarity by calculating the distance in 3D blocks. The proposed method is tested on both simulated and real hyperspectral images, the results demonstrate that the proposed method is superior to several other popular methods in HSI denoising.

Experimental Effects and Individual Differences in Linear Mixed Models: Estimating the Relationship between Spatial, Object, and Attraction Effects in Visual Attention

PubMed Central

Kliegl, Reinhold; Wei, Ping; Dambacher, Michael; Yan, Ming; Zhou, Xiaolin

2011-01-01

Linear mixed models (LMMs) provide a still underused methodological perspective on combining experimental and individual-differences research. Here we illustrate this approach with two-rectangle cueing in visual attention (Egly et al., 1994). We replicated previous experimental cue-validity effects relating to a spatial shift of attention within an object (spatial effect), to attention switch between objects (object effect), and to the attraction of attention toward the display centroid (attraction effect), also taking into account the design-inherent imbalance of valid and other trials. We simultaneously estimated variance/covariance components of subject-related random effects for these spatial, object, and attraction effects in addition to their mean reaction times (RTs). The spatial effect showed a strong positive correlation with mean RT and a strong negative correlation with the attraction effect. The analysis of individual differences suggests that slow subjects engage attention more strongly at the cued location than fast subjects. We compare this joint LMM analysis of experimental effects and associated subject-related variances and correlations with two frequently used alternative statistical procedures. PMID:21833292

Spatial Temporal Analysis Of Mine-induced Seismicity

NASA Astrophysics Data System (ADS)

Fedotova, I. V.; Yunga, S. L.

The results of analysis of influence mine-induced seismicity on state of stress of a rock mass are represented. The spatial-temporal analysis of influence of mass explosions on rock massif deformation is carried out in the territory of a mine field Yukspor of a wing of the Joined Kirovsk mine JSC "Apatite". Estimation of influence of mass explosions on a massif were determined based firstly on the parameters of natural seismicic regime, and secondly taking into consideration change of seismic energy release. After long series of explosions variations in average number of seismic events was fixed. Is proved, that with increase of a volume of rocks, involved in a deforma- tion the released energy of seismic events, and characteristic intervals of time of their preparation are also varied. At the same time, the mechanism of destruction changes also: from destruction's, of a type shift - separation before destruction's, in a quasi- solid heterogeneous massif (in oxidized zones and zones of actuated faults). Analysis of a database seismicity of a massif from 1993 to 1999 years has confirmed, that the response of a massif on explosions is connected to stress-deformations state a mas- sif and parameters of a mining working. The analysis of spatial-temporal distribution of hypocenters of seismic events has allowed to allocate migration of fissile regions of destruction after mass explosions. The researches are executed at support of the Russian foundation for basic research, - projects 00-05-64758, 01-05-65340.

Exploring the Specifications of Spatial Adjacencies and Weights in Bayesian Spatial Modeling with Intrinsic Conditional Autoregressive Priors in a Small-area Study of Fall Injuries

PubMed Central

Law, Jane

2016-01-01

Intrinsic conditional autoregressive modeling in a Bayeisan hierarchical framework has been increasingly applied in small-area ecological studies. This study explores the specifications of spatial structure in this Bayesian framework in two aspects: adjacency, i.e., the set of neighbor(s) for each area; and (spatial) weight for each pair of neighbors. Our analysis was based on a small-area study of falling injuries among people age 65 and older in Ontario, Canada, that was aimed to estimate risks and identify risk factors of such falls. In the case study, we observed incorrect adjacencies information caused by deficiencies in the digital map itself. Further, when equal weights was replaced by weights based on a variable of expected count, the range of estimated risks increased, the number of areas with probability of estimated risk greater than one at different probability thresholds increased, and model fit improved. More importantly, significance of a risk factor diminished. Further research to thoroughly investigate different methods of variable weights; quantify the influence of specifications of spatial weights; and develop strategies for better defining spatial structure of a map in small-area analysis in Bayesian hierarchical spatial modeling is recommended. PMID:29546147

Considering spatial heterogeneity in the distributed lag non-linear model when analyzing spatiotemporal data.

PubMed

Chien, Lung-Chang; Guo, Yuming; Li, Xiao; Yu, Hwa-Lung

2018-01-01

The distributed lag non-linear (DLNM) model has been frequently used in time series environmental health research. However, its functionality for assessing spatial heterogeneity is still restricted, especially in analyzing spatiotemporal data. This study proposed a solution to take a spatial function into account in the DLNM, and compared the influence with and without considering spatial heterogeneity in a case study. This research applied the DLNM to investigate non-linear lag effect up to 7 days in a case study about the spatiotemporal impact of fine particulate matter (PM 2.5 ) on preschool children's acute respiratory infection in 41 districts of northern Taiwan during 2005 to 2007. We applied two spatiotemporal methods to impute missing air pollutant data, and included the Markov random fields to analyze district boundary data in the DLNM. When analyzing the original data without a spatial function, the overall PM 2.5 effect accumulated from all lag-specific effects had a slight variation at smaller PM 2.5 measurements, but eventually decreased to relative risk significantly <1 when PM 2.5 increased. While analyzing spatiotemporal imputed data without a spatial function, the overall PM 2.5 effect did not decrease but increased in monotone as PM 2.5 increased over 20 μg/m 3 . After adding a spatial function in the DLNM, spatiotemporal imputed data conducted similar results compared with the overall effect from the original data. Moreover, the spatial function showed a clear and uneven pattern in Taipei, revealing that preschool children living in 31 districts of Taipei were vulnerable to acute respiratory infection. Our findings suggest the necessity of including a spatial function in the DLNM to make a spatiotemporal analysis available and to conduct more reliable and explainable research. This study also revealed the analytical impact if spatial heterogeneity is ignored.

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

NASA Astrophysics Data System (ADS)

Martin, D. J.

2013-12-01

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

`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.

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

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

USGS Publications Warehouse

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

2017-01-01

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

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

Exploring spatial patterns of sudden cardiac arrests in the city of Toronto using Poisson kriging and Hot Spot analyses

PubMed Central

2017-01-01

Introduction Our study looked at out-of-hospital sudden cardiac arrest events in the City of Toronto. These are relatively rare events, yet present a serious global clinical and public health problem. We report on the application of spatial methods and tools that, although relatively well known to geographers and natural resource scientists, need to become better known and used more frequently by health care researchers. Materials and methods Our data came from the population-based Rescu Epistry cardiac arrest database. We limited it to the residents of the City of Toronto who experienced sudden arrest in 2010. The data was aggregated at the Dissemination Area level, and population rates were calculated. Poisson kriging was carried out on one year of data using three different spatial weights. Kriging estimates were then compared in Hot Spot analyses. Results Spatial analysis revealed that Poisson kriging can yield reliable rates using limited data of high quality. We observed the highest rates of sudden arrests in the north and central parts of Etobicoke, western parts of North York as well as the central and southwestern parts of Scarborough while the lowest rates were found in north and eastern parts of Scarborough, downtown Toronto, and East York as well as east central parts of North York. Influence of spatial neighbours on the results did not extend past two rings of adjacent units. Conclusions Poisson kriging has the potential to be applied to a wide range of healthcare research, particularly on rare events. This approach can be successfully combined with other spatial methods. More applied research, is needed to establish a wider acceptance for this method, especially among healthcare researchers and epidemiologists. PMID:28672029

Exploring spatial patterns of sudden cardiac arrests in the city of Toronto using Poisson kriging and Hot Spot analyses.

PubMed

Przybysz, Raymond; Bunch, Martin

2017-01-01

Our study looked at out-of-hospital sudden cardiac arrest events in the City of Toronto. These are relatively rare events, yet present a serious global clinical and public health problem. We report on the application of spatial methods and tools that, although relatively well known to geographers and natural resource scientists, need to become better known and used more frequently by health care researchers. Our data came from the population-based Rescu Epistry cardiac arrest database. We limited it to the residents of the City of Toronto who experienced sudden arrest in 2010. The data was aggregated at the Dissemination Area level, and population rates were calculated. Poisson kriging was carried out on one year of data using three different spatial weights. Kriging estimates were then compared in Hot Spot analyses. Spatial analysis revealed that Poisson kriging can yield reliable rates using limited data of high quality. We observed the highest rates of sudden arrests in the north and central parts of Etobicoke, western parts of North York as well as the central and southwestern parts of Scarborough while the lowest rates were found in north and eastern parts of Scarborough, downtown Toronto, and East York as well as east central parts of North York. Influence of spatial neighbours on the results did not extend past two rings of adjacent units. Poisson kriging has the potential to be applied to a wide range of healthcare research, particularly on rare events. This approach can be successfully combined with other spatial methods. More applied research, is needed to establish a wider acceptance for this method, especially among healthcare researchers and epidemiologists.

(TUCSON, AZ) SPATIAL ANALYSIS OF SUMMER 2004 DATA FROM DEARS

EPA Science Inventory

The Detroit Exposure and Aerosol Research Study (DEARS) represents a multi-year assessment field study involving summer and winter season collection of personal, residential indoor, residential outdoor and central community monitoring measurements.

Spatial econometric analysis of factors influencing regional energy efficiency in China.

PubMed

Song, Malin; Chen, Yu; An, Qingxian

2018-05-01

Increased environmental pollution and energy consumption caused by the country's rapid development has raised considerable public concern, and has become the focus of the government and public. This study employs the super-efficiency slack-based model-data envelopment analysis (SBM-DEA) to measure the total factor energy efficiency of 30 provinces in China. The estimation model for the spatial interaction intensity of regional total factor energy efficiency is based on Wilson's maximum entropy model. The model is used to analyze the factors that affect the potential value of total factor energy efficiency using spatial dynamic panel data for 30 provinces during 2000-2014. The study found that there are differences and spatial correlations of energy efficiency among provinces and regions in China. The energy efficiency in the eastern, central, and western regions fluctuated significantly, and was mainly because of significant energy efficiency impacts on influences of industrial structure, energy intensity, and technological progress. This research is of great significance to China's energy efficiency and regional coordinated development.

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.

Remote sensing, geographical information systems, and spatial modeling for analyzing public transit services

NASA Astrophysics Data System (ADS)

Wu, Changshan

Public transit service is a promising transportation mode because of its potential to address urban sustainability. Current ridership of public transit, however, is very low in most urban regions, particularly those in the United States. This woeful transit ridership can be attributed to many factors, among which poor service quality is key. Given this, there is a need for transit planning and analysis to improve service quality. Traditionally, spatially aggregate data are utilized in transit analysis and planning. Examples include data associated with the census, zip codes, states, etc. Few studies, however, address the influences of spatially aggregate data on transit planning results. In this research, previous studies in transit planning that use spatially aggregate data are reviewed. Next, problems associated with the utilization of aggregate data, the so-called modifiable areal unit problem (MAUP), are detailed and the need for fine resolution data to support public transit planning is argued. Fine resolution data is generated using intelligent interpolation techniques with the help of remote sensing imagery. In particular, impervious surface fraction, an important socio-economic indicator, is estimated through a fully constrained linear spectral mixture model using Landsat Enhanced Thematic Mapper Plus (ETM+) data within the metropolitan area of Columbus, Ohio in the United States. Four endmembers, low albedo, high albedo, vegetation, and soil are selected to model heterogeneous urban land cover. Impervious surface fraction is estimated by analyzing low and high albedo endmembers. With the derived impervious surface fraction, three spatial interpolation methods, spatial regression, dasymetric mapping, and cokriging, are developed to interpolate detailed population density. Results suggest that cokriging applied to impervious surface is a better alternative for estimating fine resolution population density. With the derived fine resolution data, a multiple route maximal covering/shortest path (MRMCSP) model is proposed to address the tradeoff between public transit service quality and access coverage in an established bus-based transit system. Results show that it is possible to improve current transit service quality by eliminating redundant or underutilized service stops. This research illustrates that fine resolution data can be efficiently generated to support urban planning, management and analysis. Further, this detailed data may necessitate the development of new spatial optimization models for use in analysis.

Human Ecology: A Means of Environmental and Demographic Analysis in Educational Research.

ERIC Educational Resources Information Center

Olson, John Alden

The purpose of the study was to provide an ecological-demographic analysis of a suburban elementary school attendance area by examining the sociocultural elements within the spatially delimited boundaries. The area, though beyond the limits of the incorporated city, was part of the urban school district which transcended the political boundaries…

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

NASA Astrophysics Data System (ADS)

Erfanifard, Y.; Rezayan, F.

2014-10-01

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

Automation method to identify the geological structure of seabed using spatial statistic analysis of echo sounding data

NASA Astrophysics Data System (ADS)

Kwon, O.; Kim, W.; Kim, J.

2017-12-01

Recently construction of subsea tunnel has been increased globally. For safe construction of subsea tunnel, identifying the geological structure including fault at design and construction stage is more than important. Then unlike the tunnel in land, it's very difficult to obtain the data on geological structure because of the limit in geological survey. This study is intended to challenge such difficulties in a way of developing the technology to identify the geological structure of seabed automatically by using echo sounding data. When investigation a potential site for a deep subsea tunnel, there is the technical and economical limit with borehole of geophysical investigation. On the contrary, echo sounding data is easily obtainable while information reliability is higher comparing to above approaches. This study is aimed at developing the algorithm that identifies the large scale of geological structure of seabed using geostatic approach. This study is based on theory of structural geology that topographic features indicate geological structure. Basic concept of algorithm is outlined as follows; (1) convert the seabed topography to the grid data using echo sounding data, (2) apply the moving window in optimal size to the grid data, (3) estimate the spatial statistics of the grid data in the window area, (4) set the percentile standard of spatial statistics, (5) display the values satisfying the standard on the map, (6) visualize the geological structure on the map. The important elements in this study include optimal size of moving window, kinds of optimal spatial statistics and determination of optimal percentile standard. To determine such optimal elements, a numerous simulations were implemented. Eventually, user program based on R was developed using optimal analysis algorithm. The user program was designed to identify the variations of various spatial statistics. It leads to easy analysis of geological structure depending on variation of spatial statistics by arranging to easily designate the type of spatial statistics and percentile standard. This research was supported by the Korea Agency for Infrastructure Technology Advancement under the Ministry of Land, Infrastructure and Transport of the Korean government. (Project Number: 13 Construction Research T01)

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

Modelling the Effects of Land-Use Changes on Climate: a Case Study on Yamula DAM

NASA Astrophysics Data System (ADS)

Köylü, Ü.; Geymen, A.

2016-10-01

Dams block flow of rivers and cause artificial water reservoirs which affect the climate and the land use characteristics of the river basin. In this research, the effect of the huge water body obtained by Yamula Dam in Kızılırmak Basin is analysed over surrounding spatial's land use and climate change. Mann Kendal non-parametrical statistical test, Theil&Sen Slope method, Inverse Distance Weighting (IDW), Soil Conservation Service-Curve Number (SCS-CN) methods are integrated for spatial and temporal analysis of the research area. For this research humidity, temperature, wind speed, precipitation observations which are collected in 16 weather stations nearby Kızılırmak Basin are analyzed. After that these statistical information is combined by GIS data over years. An application is developed for GIS analysis in Python Programming Language and integrated with ArcGIS software. Statistical analysis calculated in the R Project for Statistical Computing and integrated with developed application. According to the statistical analysis of extracted time series of meteorological parameters, statistical significant spatiotemporal trends are observed for climate change and land use characteristics. In this study, we indicated the effect of big dams in local climate on semi-arid Yamula Dam.

Climate change and epidemics in Chinese history: A multi-scalar analysis.

PubMed

Lee, Harry F; Fei, Jie; Chan, Christopher Y S; Pei, Qing; Jia, Xin; Yue, Ricci P H

2017-02-01

This study seeks to provide further insight regarding the relationship of climate-epidemics in Chinese history through a multi-scalar analysis. Based on 5961 epidemic incidents in China during 1370-1909 CE we applied Ordinary Least Square regression and panel data regression to verify the climate-epidemic nexus over a range of spatial scales (country, macro region, and province). Results show that epidemic outbreaks were negatively correlated with the temperature in historical China at various geographic levels, while a stark reduction in the correlational strength was observed at lower geographic levels. Furthermore, cooling drove up epidemic outbreaks in northern and central China, where population pressure reached a clear threshold for amplifying the vulnerability of epidemic outbreaks to climate change. Our findings help to illustrate the modifiable areal unit and the uncertain geographic context problems in climate-epidemics research. Researchers need to consider the scale effect in the course of statistical analyses, which are currently predominantly conducted on a national/single scale; and also the importance of how the study area is delineated, an issue which is rarely discussed in the climate-epidemics literature. Future research may leverage our results and provide a cross-analysis with those derived from spatial analysis. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2016-11-01

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

Object-based vegetation classification with high resolution remote sensing imagery

NASA Astrophysics Data System (ADS)

Yu, Qian

Vegetation species are valuable indicators to understand the earth system. Information from mapping of vegetation species and community distribution at large scales provides important insight for studying the phenological (growth) cycles of vegetation and plant physiology. Such information plays an important role in land process modeling including climate, ecosystem and hydrological models. The rapidly growing remote sensing technology has increased its potential in vegetation species mapping. However, extracting information at a species level is still a challenging research topic. I proposed an effective method for extracting vegetation species distribution from remotely sensed data and investigated some ways for accuracy improvement. The study consists of three phases. Firstly, a statistical analysis was conducted to explore the spatial variation and class separability of vegetation as a function of image scale. This analysis aimed to confirm that high resolution imagery contains the information on spatial vegetation variation and these species classes can be potentially separable. The second phase was a major effort in advancing classification by proposing a method for extracting vegetation species from high spatial resolution remote sensing data. The proposed classification employs an object-based approach that integrates GIS and remote sensing data and explores the usefulness of ancillary information. The whole process includes image segmentation, feature generation and selection, and nearest neighbor classification. The third phase introduces a spatial regression model for evaluating the mapping quality from the above vegetation classification results. The effects of six categories of sample characteristics on the classification uncertainty are examined: topography, sample membership, sample density, spatial composition characteristics, training reliability and sample object features. This evaluation analysis answered several interesting scientific questions such as (1) whether the sample characteristics affect the classification accuracy and how significant if it does; (2) how much variance of classification uncertainty can be explained by above factors. This research is carried out on a hilly peninsular area in Mediterranean climate, Point Reyes National Seashore (PRNS) in Northern California. The area mainly consists of a heterogeneous, semi-natural broadleaf and conifer woodland, shrub land, and annual grassland. A detailed list of vegetation alliances is used in this study. Research results from the first phase indicates that vegetation spatial variation as reflected by the average local variance (ALV) keeps a high level of magnitude between 1 m and 4 m resolution. (Abstract shortened by UMI.)

Analysis of spatial density dependence in gypsy moth mortality

Treesearch

Andrew Liebhold; Joseph S. Elkinton

1991-01-01

The gypsy moth is perhaps the most widely studied forest insect in the world and much of this research has focused on various aspects of population dynamics. But despite this voluminous amount of research we still lack a good understanding of which, if any, natural enemy species regulate gypsy moth populations. The classical approach to analyzing insect population...

Network Ethnography and the "Cyberflâneur": Evolving Policy Sociology in Education

ERIC Educational Resources Information Center

Hogan, Anna

2016-01-01

This paper makes the argument that new global spatialities and new governance structures in education have important implications for how we think about education policy and do education policy analysis. This context necessitates that researchers engage in new methodologies to ensure that there is a suitable link between their research problem and…

A Spatial Hedonic Analysis of the Effects of Wind Energy Facilities on Surrounding Property Values in the United States

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

Hoen, Ben; Wiser, Ryan; Cappers, Peter

2013-08-21

This report summarizes a new analysis, building on previously published research, about wind energy’s effects on residential property values. This study helps fill research gaps by collecting and analyzing data from 27 counties across nine U.S. states, related to 67 different wind facilities, and constructs a pooled model that investigates average effects near the turbines across the sample while controlling for local variables, such as sale prices of nearby homes.

Landsat Thematic Mapper studies of land cover spatial variability related to hydrology

NASA Technical Reports Server (NTRS)

Wharton, S.; Ormsby, J.; Salomonson, V.; Mulligan, P.

1984-01-01

Past accomplishments involving remote sensing based land-cover analysis for hydrologic applications are reviewed. Ongoing research in exploiting the increased spatial, radiometric, and spectral capabilities afforded by the TM on Landsats 4 and 5 is considered. Specific studies to compare MSS and TM for urbanizing watersheds, wetlands, and floodplain mapping situations show that only a modest improvement in classification accuracy is achieved via statistical per pixel multispectral classifiers. The limitations of current approaches to multispectral classification are illustrated. The objectives, background, and progress in the development of an alternative analysis approach for defining inputs to urban hydrologic models using TM are discussed.

Power quality analysis based on spatial correlation

NASA Astrophysics Data System (ADS)

Li, Jiangtao; Zhao, Gang; Liu, Haibo; Li, Fenghou; Liu, Xiaoli

2018-03-01

With the industrialization and urbanization, the status of electricity in the production and life is getting higher and higher. So the prediction of power quality is the more potential significance. Traditional power quality analysis methods include: power quality data compression, disturbance event pattern classification, disturbance parameter calculation. Under certain conditions, these methods can predict power quality. This paper analyses the temporal variation of power quality of one provincial power grid in China from time angle. The distribution of power quality was analyzed based on spatial autocorrelation. This paper tries to prove that the research idea of geography is effective for mining the potential information of power quality.

Spatial regression analysis of traffic crashes in Seoul.

PubMed

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

2016-06-01

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

Spatial modeling of cutaneous leishmaniasis in the Andean region of Colombia

PubMed Central

Pérez-Flórez, Mauricio; Ocampo, Clara Beatriz; Valderrama-Ardila, Carlos; Alexander, Neal

2016-01-01

The objective of this research was to identify environmental risk factors for cutaneous leishmaniasis (CL) in Colombia and map high-risk municipalities. The study area was the Colombian Andean region, comprising 715 rural and urban municipalities. We used 10 years of CL surveillance: 2000-2009. We used spatial-temporal analysis - conditional autoregressive Poisson random effects modelling - in a Bayesian framework to model the dependence of municipality-level incidence on land use, climate, elevation and population density. Bivariable spatial analysis identified rainforests, forests and secondary vegetation, temperature, and annual precipitation as positively associated with CL incidence. By contrast, livestock agroecosystems and temperature seasonality were negatively associated. Multivariable analysis identified land use - rainforests and agro-livestock - and climate - temperature, rainfall and temperature seasonality - as best predictors of CL. We conclude that climate and land use can be used to identify areas at high risk of CL and that this approach is potentially applicable elsewhere in Latin America. PMID:27355214

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

PubMed

Carrer, Francesco

2017-01-01

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

Development of a Heterogenic Distributed Environment for Spatial Data Processing Using Cloud Technologies

NASA Astrophysics Data System (ADS)

Garov, A. S.; Karachevtseva, I. P.; Matveev, E. V.; Zubarev, A. E.; Florinsky, I. V.

2016-06-01

We are developing a unified distributed communication environment for processing of spatial data which integrates web-, desktop- and mobile platforms and combines volunteer computing model and public cloud possibilities. The main idea is to create a flexible working environment for research groups, which may be scaled according to required data volume and computing power, while keeping infrastructure costs at minimum. It is based upon the "single window" principle, which combines data access via geoportal functionality, processing possibilities and communication between researchers. Using an innovative software environment the recently developed planetary information system (http://cartsrv.mexlab.ru/geoportal) will be updated. The new system will provide spatial data processing, analysis and 3D-visualization and will be tested based on freely available Earth remote sensing data as well as Solar system planetary images from various missions. Based on this approach it will be possible to organize the research and representation of results on a new technology level, which provides more possibilities for immediate and direct reuse of research materials, including data, algorithms, methodology, and components. The new software environment is targeted at remote scientific teams, and will provide access to existing spatial distributed information for which we suggest implementation of a user interface as an advanced front-end, e.g., for virtual globe system.

Analysis and Research on Spatial Data Storage Model Based on Cloud Computing Platform

NASA Astrophysics Data System (ADS)

Hu, Yong

2017-12-01

In this paper, the data processing and storage characteristics of cloud computing are analyzed and studied. On this basis, a cloud computing data storage model based on BP neural network is proposed. In this data storage model, it can carry out the choice of server cluster according to the different attributes of the data, so as to complete the spatial data storage model with load balancing function, and have certain feasibility and application advantages.

Statistical analysis of mesoscale rainfall: Dependence of a random cascade generator on large-scale forcing

NASA Technical Reports Server (NTRS)

Over, Thomas, M.; Gupta, Vijay K.

1994-01-01

Under the theory of independent and identically distributed random cascades, the probability distribution of the cascade generator determines the spatial and the ensemble properties of spatial rainfall. Three sets of radar-derived rainfall data in space and time are analyzed to estimate the probability distribution of the generator. A detailed comparison between instantaneous scans of spatial rainfall and simulated cascades using the scaling properties of the marginal moments is carried out. This comparison highlights important similarities and differences between the data and the random cascade theory. Differences are quantified and measured for the three datasets. Evidence is presented to show that the scaling properties of the rainfall can be captured to the first order by a random cascade with a single parameter. The dependence of this parameter on forcing by the large-scale meteorological conditions, as measured by the large-scale spatial average rain rate, is investigated for these three datasets. The data show that this dependence can be captured by a one-to-one function. Since the large-scale average rain rate can be diagnosed from the large-scale dynamics, this relationship demonstrates an important linkage between the large-scale atmospheric dynamics and the statistical cascade theory of mesoscale rainfall. Potential application of this research to parameterization of runoff from the land surface and regional flood frequency analysis is briefly discussed, and open problems for further research are presented.

Geoscience information integration and visualization research of Shandong Province, China based on ArcGIS engine

NASA Astrophysics Data System (ADS)

Xu, Mingzhu; Gao, Zhiqiang; Ning, Jicai

2014-10-01

To improve the access efficiency of geoscience data, efficient data model and storage solutions should be used. Geoscience data is usually classified by format or coordinate system in existing storage solutions. When data is large, it is not conducive to search the geographic features. In this study, a geographical information integration system of Shandong province, China was developed based on the technology of ArcGIS Engine, .NET, and SQL Server. It uses Geodatabase spatial data model and ArcSDE to organize and store spatial and attribute data and establishes geoscience database of Shangdong. Seven function modules were designed: map browse, database and subject management, layer control, map query, spatial analysis and map symbolization. The system's characteristics of can be browsed and managed by geoscience subjects make the system convenient for geographic researchers and decision-making departments to use the data.

Hard X-ray Microscopy with sub 30 nm Spatial Resolution

NASA Astrophysics Data System (ADS)

Tang, Mau-Tsu; Song, Yen-Fang; Yin, Gung-Chian; Chen, Fu-Rong; Chen, Jian-Hua; Chen, Yi-Ming; Liang, Keng S.; Duewer, F.; Yun, Wenbing

2007-01-01

A transmission X-ray microscope (TXM) has been installed at the BL01B beamline at National Synchrotron Radiation Research Center in Taiwan. This state-of-the-art TXM operational in a range 8-11 keV provides 2D images and 3D tomography with spatial resolution 60 nm, and with the Zernike-phase contrast mode for imaging light materials such as biological specimens. A spatial resolution of the TXM better than 30 nm, apparently the best result in hard X-ray microscopy, has been achieved by employing the third diffraction order of the objective zone plate. The TXM has been applied in diverse research fields, including analysis of failure mechanisms in microelectronic devices, tomographic structures of naturally grown photonic specimens, and the internal structure of fault zone gouges from an earthquake core. Here we discuss the scope and prospects of the project, and the progress of the TXM in NSRRC.

Comprehensive Flood Plain Studies Using Spatial Data Management Techniques.

DTIC Science & Technology

1978-06-01

Hydrologic Engineer- ing Center computer programs that forecast urban storm water quality and dynamic in- stream water quality response to waste...determination. Water Quality The water quality analysis planned for the pilot study includes urban storm water quality forecasting and in-streamn...analysis is performed under the direction of Tony Thomas. Chief, Research Branch, by Jess Abbott for storm water quality analysis, R. G. Willey for

Spatial environmental risk factors for pedestrian injury collisions in Ciudad Juárez, Mexico (2008-2009): implications for urban planning.

PubMed

Fuentes, Cesar Mario; Hernandez, Vladimir

2013-01-01

The aim of this study is to examine the spatial distribution of pedestrian injury collisions and analyse the environmental (social and physical) risk factors in Ciudad Juarez, Mexico. More specifically, this study investigates the influence of land use, density, traffic and socio-economic characteristics. This cross sectional study is based on pedestrian injury collision data that were collected by the Municipal Transit Police during 2008-2009. This research presents an analysis of vehicle-pedestrian collisions and their spatial risk determinants using mixed methods that included (1) spatial/geographical information systems (GIS) analysis of pedestrian collision data and (2) ordinary least squares (OLS) regression analysis to explain the density of pedestrian collisions data. In our model, we found a higher probability for pedestrian collisions in census tracts with population and employment density, large concentration of commercial/retail land uses and older people (65 and more). Interventions to alleviate this situation including transportation planning such as decentralisation of municipal transport system, investment in road infrastructure - density of traffic lights, pedestrian crossing, road design, improves lane demarcation. Besides, land use planning interventions should be implemented in commercial/retail areas, in particular separating pedestrian and vehicular spaces.

Modality-specificity of Selective Attention Networks.

PubMed

Stewart, Hannah J; Amitay, Sygal

2015-01-01

To establish the modality specificity and generality of selective attention networks. Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs. The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled "general attention." The third component was labeled "auditory attention," as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as "spatial orienting" and "spatial conflict," respectively-they were comprised of orienting and conflict resolution measures from the vANT, aANT, and TAiL attend-location task-all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location). These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific.

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

PubMed Central

2011-01-01

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

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.

Spatial analysis of storm depths from an Arizona raingage network

NASA Technical Reports Server (NTRS)

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

1986-01-01

Eight years of summer rainstorm observations are analyzed by a dense network of 93 raingages operated by the U.S. Department of Agriculture, Agricultural Research Service, in the 150 km Walnut Gulch experimental catchment near Tucson, Arizona. Storms are defined by the total depths collected at each raingage during the noon-to-noon period for which there was depth recorded at any of the gages. For each of the resulting 428 storm days, the gage depths are interpolated onto a dense grid and the resulting random field analyzed to obtain moments, isohyetal plots, spatial correlation function, variance function, and the spatial distribution of storm depth.

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

PubMed

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

2015-09-01

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

Modeling the impact of spatial relationships on horizontal curve safety.

PubMed

Findley, Daniel J; Hummer, Joseph E; Rasdorf, William; Zegeer, Charles V; Fowler, Tyler J

2012-03-01

The curved segments of roadways are more hazardous because of the additional centripetalforces exerted on a vehicle, driver expectations, and other factors. The safety of a curve is dependent on various factors, most notably by geometric factors, but the location of a curve in relation to other curves is also thought to influence the safety of those curves because of a driver's expectation to encounter additional curves. The link between an individual curve's geometric characteristics and its safety performance has been established, but spatial considerations are typically not included in a safety analysis. The spatial considerations included in this research consisted of four components: distance to adjacent curves, direction of turn of the adjacent curves, and radius and length of the adjacent curves. The primary objective of this paper is to quantify the spatial relationship between adjacent horizontal curves and horizontal curve safety using a crash modification factor. Doing so enables a safety professional to more accurately estimate safety to allocate funding to reduce or prevent future collisions and more efficiently design new roadway sections to minimize crash risk where there will be a series of curves along a route. The most important finding from this research is the statistical significance of spatial considerations for the prediction of horizontal curve safety. The distances to adjacent curves were found to be a reliable predictor of observed collisions. This research recommends a model which utilizes spatial considerations for horizontal curve safety prediction in addition to current Highway Safety Manual prediction capabilities using individual curve geometric features. Copyright © 2011 Elsevier Ltd. All rights reserved.

Spatial abilities, Earth science conceptual understanding, and psychological gender of university non-science majors

NASA Astrophysics Data System (ADS)

Black, Alice A. (Jill)

Research has shown the presence of many Earth science misconceptions and conceptual difficulties that may impede concept understanding, and has also identified a number of categories of spatial ability. Although spatial ability has been linked to high performance in science, some researchers believe it has been overlooked in traditional education. Evidence exists that spatial ability can be improved. This correlational study investigated the relationship among Earth science conceptual understanding, three types of spatial ability, and psychological gender, a self-classification that reflects socially-accepted personality and gender traits. A test of Earth science concept understanding, the Earth Science Concepts (ESC) test, was developed and field tested from 2001 to 2003 in 15 sections of university classes. Criterion validity was .60, significant at the .01 level. Spearman/Brown reliability was .74 and Kuder/Richardson reliability was .63. The Purdue Visualization of Rotations (PVOR) (mental rotation), the Group Embedded Figures Test (GEFT) (spatial perception), the Differential Aptitude Test: Space Relations (DAT) (spatial visualization), and the Bem Inventory (BI) (psychological gender) were administered to 97 non-major university students enrolled in undergraduate science classes. Spearman correlations revealed moderately significant correlations at the .01 level between ESC scores and each of the three spatial ability test scores. Stepwise regression analysis indicated that PVOR scores were the best predictor of ESC scores, and showed that spatial ability scores accounted for 27% of the total variation in ESC scores. Spatial test scores were moderately or weakly correlated with each other. No significant correlations were found among BI scores and other test scores. Scantron difficulty analysis of ESC items produced difficulty ratings ranging from 33.04 to 96.43, indicating the percentage of students who answered incorrectly. Mean score on the ESC was 34%, indicating that the non-majors tested exhibited many Earth science misconceptions and conceptual difficulties. A number of significant results were found when independent t-tests and correlations were conducted among test scores and demographic variables. The number of previous university Earth science courses was significantly related to ESC scores. Preservice elementary/middle majors differed significantly in several ways from other non-majors, and several earlier results were not supported. Results of this study indicate that an important opportunity may exist to improve Earth science conceptual understanding by focusing on spatial ability, a cognitive ability that has heretofore not been directly addressed in schools.

Community design and transportation safety

DOT National Transportation Integrated Search

2011-03-06

In this research we carry out a spatial analysis of 11 years of crash data in 24 medium-sized : California cities. The cities were selected from an initial database of over 150 California : cities to best represent a geographically diverse collection...

Landscape analysis of pesticide use patterns and ecological exposure

EPA Science Inventory

Background/Question/Methods The pesticide exposure landscape in the US is spatially and temporally complex. Researchers studying ecological exposure and effects of pesticides must consider a number of dimensions when framing experiments and conducting assessments. These dimension...

Spatial ability of slow learners based on Hubert Maier theory

NASA Astrophysics Data System (ADS)

Permatasari, I.; Pramudya, I.; Kusmayadi, T. A.

2018-03-01

Slow learners are children who have low learning achievement (under the average of normal children) in one or all of the academic field, but they are not classified as a mentally retarded children. Spatial ability developed according to age and level of knowledge possessed, both from the neighborhood and formal education. Analyzing the spatial ability of students is important for teachers, as an effort to improve the quality of learning for slow learners. Especially on the implementation of inclusion school which is developing in Indonesia. This research used a qualitative method and involved slow learner students as the subject. Based on the data analysis it was found the spatial ability of slow learners, there were: spatial perception, students were able to describe the other shape of object when its position changed; spatial visualisation, students were able to describe the materials that construct an object; mental rotation, students cannot describe the object being rotated; spatial relation, students cannot describe the relations of same objects; spatial orientation, students were able to describe object from the others perspective.

Race, deprivation, and immigrant isolation: The spatial demography of air-toxic clusters in the continental United States.

PubMed

Liévanos, Raoul S

2015-11-01

This article contributes to environmental inequality outcomes research on the spatial and demographic factors associated with cumulative air-toxic health risks at multiple geographic scales across the United States. It employs a rigorous spatial cluster analysis of census tract-level 2005 estimated lifetime cancer risk (LCR) of ambient air-toxic emissions from stationary (e.g., facility) and mobile (e.g., vehicular) sources to locate spatial clusters of air-toxic LCR risk in the continental United States. It then tests intersectional environmental inequality hypotheses on the predictors of tract presence in air-toxic LCR clusters with tract-level principal component factor measures of economic deprivation by race and immigrant status. Logistic regression analyses show that net of controls, isolated Latino immigrant-economic deprivation is the strongest positive demographic predictor of tract presence in air-toxic LCR clusters, followed by black-economic deprivation and isolated Asian/Pacific Islander immigrant-economic deprivation. Findings suggest scholarly and practical implications for future research, advocacy, and policy. Copyright © 2015 Elsevier Inc. All rights reserved.

75 years of dryland science: Trends and gaps in arid ecology literature.

PubMed

Greenville, Aaron C; Dickman, Chris R; Wardle, Glenda M

2017-01-01

Growth in the publication of scientific articles is occurring at an exponential rate, prompting a growing need to synthesise information in a timely manner to combat urgent environmental problems and guide future research. Here, we undertake a topic analysis of dryland literature over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging. Four topics-wetlands, mammal ecology, litter decomposition and spatial modelling, were identified as 'hot topics' that showed higher than average growth in publications from 1940 to 2015. Five topics-remote sensing, climate, habitat and spatial, agriculture and soils-microbes, were identified as 'cold topics', with lower than average growth over the survey period, but higher than average numbers of publications. Topics in arid ecology clustered into seven broad groups on word-based similarity. These groups ranged from mammal ecology and population genetics, broad-scale management and ecosystem modelling, plant ecology, agriculture and ecophysiology, to populations and paleoclimate. These patterns may reflect trends in the field of ecology more broadly. We also identified two broad research gaps in arid ecology: population genetics, and habitat and spatial research. Collaborations between population genetics and ecologists and investigations of ecological processes across spatial scales would contribute profitably to the advancement of arid ecology and to ecology more broadly.

Multi-scaling allometric analysis for urban and regional development

NASA Astrophysics Data System (ADS)

Chen, Yanguang

2017-01-01

The concept of allometric growth is based on scaling relations, and it has been applied to urban and regional analysis for a long time. However, most allometric analyses were devoted to the single proportional relation between two elements of a geographical system. Few researches focus on the allometric scaling of multielements. In this paper, a process of multiscaling allometric analysis is developed for the studies on spatio-temporal evolution of complex systems. By means of linear algebra, general system theory, and by analogy with the analytical hierarchy process, the concepts of allometric growth can be integrated with the ideas from fractal dimension. Thus a new methodology of geo-spatial analysis and the related theoretical models emerge. Based on the least squares regression and matrix operations, a simple algorithm is proposed to solve the multiscaling allometric equation. Applying the analytical method of multielement allometry to Chinese cities and regions yields satisfying results. A conclusion is reached that the multiscaling allometric analysis can be employed to make a comprehensive evaluation for the relative levels of urban and regional development, and explain spatial heterogeneity. The notion of multiscaling allometry may enrich the current theory and methodology of spatial analyses of urban and regional evolution.

PHYLOGEOrec: A QGIS plugin for spatial phylogeographic reconstruction from phylogenetic tree and geographical information data

NASA Astrophysics Data System (ADS)

Nashrulloh, Maulana Malik; Kurniawan, Nia; Rahardi, Brian

2017-11-01

The increasing availability of genetic sequence data associated with explicit geographic and environment (including biotic and abiotic components) information offers new opportunities to study the processes that shape biodiversity and its patterns. Developing phylogeography reconstruction, by integrating phylogenetic and biogeographic knowledge, provides richer and deeper visualization and information on diversification events than ever before. Geographical information systems such as QGIS provide an environment for spatial modeling, analysis, and dissemination by which phylogenetic models can be explicitly linked with their associated spatial data, and subsequently, they will be integrated with other related georeferenced datasets describing the biotic and abiotic environment. We are introducing PHYLOGEOrec, a QGIS plugin for building spatial phylogeographic reconstructions constructed from phylogenetic tree and geographical information data based on QGIS2threejs. By using PHYLOGEOrec, researchers can integrate existing phylogeny and geographical information data, resulting in three-dimensional geographic visualizations of phylogenetic trees in the Keyhole Markup Language (KML) format. Such formats can be overlaid on a map using QGIS and finally, spatially viewed in QGIS by means of a QGIS2threejs engine for further analysis. KML can also be viewed in reputable geobrowsers with KML-support (i.e., Google Earth).

Spatial variability of the Black Sea surface temperature from high resolution modeling and satellite measurements

NASA Astrophysics Data System (ADS)

Mizyuk, Artem; Senderov, Maxim; Korotaev, Gennady

2016-04-01

Large number of numerical ocean models were implemented for the Black Sea basin during last two decades. They reproduce rather similar structure of synoptical variability of the circulation. Since 00-s numerical studies of the mesoscale structure are carried out using high performance computing (HPC). With the growing capacity of computing resources it is now possible to reconstruct the Black Sea currents with spatial resolution of several hundreds meters. However, how realistic these results can be? In the proposed study an attempt is made to understand which spatial scales are reproduced by ocean model in the Black Sea. Simulations are made using parallel version of NEMO (Nucleus for European Modelling of the Ocean). A two regional configurations with spatial resolutions 5 km and 2.5 km are described. Comparison of the SST from simulations with two spatial resolutions shows rather qualitative difference of the spatial structures. Results of high resolution simulation are compared also with satellite observations and observation-based products from Copernicus using spatial correlation and spectral analysis. Spatial scales of correlations functions for simulated and observed SST are rather close and differs much from satellite SST reanalysis. Evolution of spectral density for modelled SST and reanalysis showed agreed time periods of small scales intensification. Using of the spectral analysis for satellite measurements is complicated due to gaps. The research leading to this results has received funding from Russian Science Foundation (project № 15-17-20020)

Heterogeneous Optimization Framework: Reproducible Preprocessing of Multi-Spectral Clinical MRI for Neuro-Oncology Imaging Research.

PubMed

Milchenko, Mikhail; Snyder, Abraham Z; LaMontagne, Pamela; Shimony, Joshua S; Benzinger, Tammie L; Fouke, Sarah Jost; Marcus, Daniel S

2016-07-01

Neuroimaging research often relies on clinically acquired magnetic resonance imaging (MRI) datasets that can originate from multiple institutions. Such datasets are characterized by high heterogeneity of modalities and variability of sequence parameters. This heterogeneity complicates the automation of image processing tasks such as spatial co-registration and physiological or functional image analysis. Given this heterogeneity, conventional processing workflows developed for research purposes are not optimal for clinical data. In this work, we describe an approach called Heterogeneous Optimization Framework (HOF) for developing image analysis pipelines that can handle the high degree of clinical data non-uniformity. HOF provides a set of guidelines for configuration, algorithm development, deployment, interpretation of results and quality control for such pipelines. At each step, we illustrate the HOF approach using the implementation of an automated pipeline for Multimodal Glioma Analysis (MGA) as an example. The MGA pipeline computes tissue diffusion characteristics of diffusion tensor imaging (DTI) acquisitions, hemodynamic characteristics using a perfusion model of susceptibility contrast (DSC) MRI, and spatial cross-modal co-registration of available anatomical, physiological and derived patient images. Developing MGA within HOF enabled the processing of neuro-oncology MR imaging studies to be fully automated. MGA has been successfully used to analyze over 160 clinical tumor studies to date within several research projects. Introduction of the MGA pipeline improved image processing throughput and, most importantly, effectively produced co-registered datasets that were suitable for advanced analysis despite high heterogeneity in acquisition protocols.

Using GIS for spatial analysis of rectal lesions in the human body.

PubMed

Garb, Jane L; Ganai, Sabha; Skinner, Ric; Boyd, Christopher S; Wait, Richard B

2007-03-15

Geographic Information Systems (GIS) have been used in a wide variety of applications to integrate data and explore the spatial relationship of geographic features. Traditionally this has referred to features on the surface of the earth. However, it is possible to apply GIS in medicine, at the scale of the human body, to visualize and analyze anatomic and clinical features. In the present study we used GIS to examine the findings of transanal endoscopic microsurgery (TEM), a minimally-invasive procedure to locate and remove both benign and cancerous lesions of the rectum. Our purpose was to determine whether anatomic features of the human rectum and clinical findings at the time of surgery could be rendered in a GIS and spatially analyzed for their relationship to clinical outcomes. Maps of rectal topology were developed in two and three dimensions. These maps highlight anatomic features of the rectum and the location of lesions found on TEM. Spatial analysis demonstrated a significant relationship between anatomic location of the lesion and procedural failure. This study demonstrates the feasibility of rendering anatomical locations and clinical events in a GIS and its value in clinical research. This allows the visualization and spatial analysis of clinical and pathologic features, increasing our awareness of the relationship between anatomic features and clinical outcomes as well as enhancing our understanding and management of this disease process.

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

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

Using GIS for spatial analysis of rectal lesions in the human body

PubMed Central

Garb, Jane L; Ganai, Sabha; Skinner, Ric; Boyd, Christopher S; Wait, Richard B

2007-01-01

Background Geographic Information Systems (GIS) have been used in a wide variety of applications to integrate data and explore the spatial relationship of geographic features. Traditionally this has referred to features on the surface of the earth. However, it is possible to apply GIS in medicine, at the scale of the human body, to visualize and analyze anatomic and clinical features. In the present study we used GIS to examine the findings of transanal endoscopic microsurgery (TEM), a minimally-invasive procedure to locate and remove both benign and cancerous lesions of the rectum. Our purpose was to determine whether anatomic features of the human rectum and clinical findings at the time of surgery could be rendered in a GIS and spatially analyzed for their relationship to clinical outcomes. Results Maps of rectal topology were developed in two and three dimensions. These maps highlight anatomic features of the rectum and the location of lesions found on TEM. Spatial analysis demonstrated a significant relationship between anatomic location of the lesion and procedural failure. Conclusion This study demonstrates the feasibility of rendering anatomical locations and clinical events in a GIS and its value in clinical research. This allows the visualization and spatial analysis of clinical and pathologic features, increasing our awareness of the relationship between anatomic features and clinical outcomes as well as enhancing our understanding and management of this disease process. PMID:17362510

PageRank versatility analysis of multilayer modality-based network for exploring the evolution of oil-water slug flow.

PubMed

Gao, Zhong-Ke; Dang, Wei-Dong; Li, Shan; Yang, Yu-Xuan; Wang, Hong-Tao; Sheng, Jing-Ran; Wang, Xiao-Fan

2017-07-14

Numerous irregular flow structures exist in the complicated multiphase flow and result in lots of disparate spatial dynamical flow behaviors. The vertical oil-water slug flow continually attracts plenty of research interests on account of its significant importance. Based on the spatial transient flow information acquired through our designed double-layer distributed-sector conductance sensor, we construct multilayer modality-based network to encode the intricate spatial flow behavior. Particularly, we calculate the PageRank versatility and multilayer weighted clustering coefficient to quantitatively explore the inferred multilayer modality-based networks. Our analysis allows characterizing the complicated evolution of oil-water slug flow, from the opening formation of oil slugs, to the succedent inter-collision and coalescence among oil slugs, and then to the dispersed oil bubbles. These properties render our developed method particularly powerful for mining the essential flow features from the multilayer sensor measurements.

Spatial Phase Imaging

NASA Technical Reports Server (NTRS)

2006-01-01

Frequently, scientists grow crystals by dissolving a protein in a specific liquid solution, and then allowing that solution to evaporate. The methods used next have been, variously, invasive (adding a dye that is absorbed by the protein), destructive (crushing protein/salt-crystal mixtures and observing differences between the crushing of salt and protein), or costly and time-consuming (X-ray crystallography). In contrast to these methods, a new technology for monitoring protein growth, developed in part through NASA Small Business Innovation Research (SBIR) funding from Marshall Space Flight Center, is noninvasive, nondestructive, rapid, and more cost effective than X-ray analysis. The partner for this SBIR, Photon-X, Inc., of Huntsville, Alabama, developed spatial phase imaging technology that can monitor crystal growth in real time and in an automated mode. Spatial phase imaging scans for flaws quickly and produces a 3-D structured image of a crystal, showing volumetric growth analysis for future automated growth.

Quantify Lateral Dispersion and Turbulent Mixing by Spatial Array of chi-EM-APEX Floats

DTIC Science & Technology

2013-09-30

pattern), 18-hour background field on the R/V Oceanus. ii) 10 km, 4-hour butterfly following dye on R/V Endeavor. iii) Dye following to track the...analysis of drogue observations, Deep- Sea Research, 23, 349-352. PUBLICATIONS (wholly or in part supported by this grant) Sanford, T.B. (2013...Spatial Structure of Thermocline and Abyssal Internal Waves, Deep- Sea Res. Part II. 85, 195-209. [published, refereed] Szuts, Z.B. and T. B. Sanford

Crime Modeling using Spatial Regression Approach

NASA Astrophysics Data System (ADS)

Saleh Ahmar, Ansari; Adiatma; Kasim Aidid, M.

2018-01-01

Act of criminality in Indonesia increased both variety and quantity every year. As murder, rape, assault, vandalism, theft, fraud, fencing, and other cases that make people feel unsafe. Risk of society exposed to crime is the number of reported cases in the police institution. The higher of the number of reporter to the police institution then the number of crime in the region is increasing. In this research, modeling criminality in South Sulawesi, Indonesia with the dependent variable used is the society exposed to the risk of crime. Modelling done by area approach is the using Spatial Autoregressive (SAR) and Spatial Error Model (SEM) methods. The independent variable used is the population density, the number of poor population, GDP per capita, unemployment and the human development index (HDI). Based on the analysis using spatial regression can be shown that there are no dependencies spatial both lag or errors in South Sulawesi.

The computational worm: spatial orientation and its neuronal basis in C. elegans.

PubMed

Lockery, Shawn R

2011-10-01

Spatial orientation behaviors in animals are fundamental for survival but poorly understood at the neuronal level. The nematode Caenorhabditis elegans orients to a wide range of stimuli and has a numerically small and well-described nervous system making it advantageous for investigating the mechanisms of spatial orientation. Recent work by the C. elegans research community has identified essential computational elements of the neural circuits underlying two orientation strategies that operate in five different sensory modalities. Analysis of these circuits reveals novel motifs including simple circuits for computing temporal derivatives of sensory input and for integrating sensory input with behavioral state to generate adaptive behavior. These motifs constitute hypotheses concerning the identity and functionality of circuits controlling spatial orientation in higher organisms. Copyright © 2011 Elsevier Ltd. All rights reserved.

Exploring the Positive Utility of Travel and Mode Choice

DOT National Transportation Integrated Search

2017-08-01

Why do people travel? Underlying most travel behavior research is the derived-demand paradigm of travel analysis, which assumes that travel demand is derived from the demand for spatially separated activities, traveling is a means to an end (reaching...

GIS-Based System of Hydrologic and Hydraulic Applications for Highway Engineering

DOT National Transportation Integrated Search

1999-10-01

In this research project, a GIS has been developed to assist in the design of highway drainage facilities by utilizing hydrologic spatial data to calculate the input parameters for standard hydrologic software packages. This GIS reduces the analysis ...

Protecting Location Privacy for Outsourced Spatial Data in Cloud Storage

PubMed Central

Gui, Xiaolin; An, Jian; Zhao, Jianqiang; Zhang, Xuejun

2014-01-01

As cloud computing services and location-aware devices are fully developed, a large amount of spatial data needs to be outsourced to the cloud storage provider, so the research on privacy protection for outsourced spatial data gets increasing attention from academia and industry. As a kind of spatial transformation method, Hilbert curve is widely used to protect the location privacy for spatial data. But sufficient security analysis for standard Hilbert curve (SHC) is seldom proceeded. In this paper, we propose an index modification method for SHC (SHC∗) and a density-based space filling curve (DSC) to improve the security of SHC; they can partially violate the distance-preserving property of SHC, so as to achieve better security. We formally define the indistinguishability and attack model for measuring the privacy disclosure risk of spatial transformation methods. The evaluation results indicate that SHC∗ and DSC are more secure than SHC, and DSC achieves the best index generation performance. PMID:25097865

Protecting location privacy for outsourced spatial data in cloud storage.

PubMed

Tian, Feng; Gui, Xiaolin; An, Jian; Yang, Pan; Zhao, Jianqiang; Zhang, Xuejun

2014-01-01

As cloud computing services and location-aware devices are fully developed, a large amount of spatial data needs to be outsourced to the cloud storage provider, so the research on privacy protection for outsourced spatial data gets increasing attention from academia and industry. As a kind of spatial transformation method, Hilbert curve is widely used to protect the location privacy for spatial data. But sufficient security analysis for standard Hilbert curve (SHC) is seldom proceeded. In this paper, we propose an index modification method for SHC (SHC(∗)) and a density-based space filling curve (DSC) to improve the security of SHC; they can partially violate the distance-preserving property of SHC, so as to achieve better security. We formally define the indistinguishability and attack model for measuring the privacy disclosure risk of spatial transformation methods. The evaluation results indicate that SHC(∗) and DSC are more secure than SHC, and DSC achieves the best index generation performance.

The influence of the interactions between anthropogenic activities and multiple ecological factors on land surface temperatures of urban forests

NASA Astrophysics Data System (ADS)

Ren, Y.

2017-12-01

Context Land surface temperatures (LSTs) spatio-temporal distribution pattern of urban forests are influenced by many ecological factors; the identification of interaction between these factors can improve simulations and predictions of spatial patterns of urban cold islands. This quantitative research requires an integrated method that combines multiple sources data with spatial statistical analysis. Objectives The purpose of this study was to clarify urban forest LST influence interaction between anthropogenic activities and multiple ecological factors using cluster analysis of hot and cold spots and Geogdetector model. We introduced the hypothesis that anthropogenic activity interacts with certain ecological factors, and their combination influences urban forests LST. We also assumed that spatio-temporal distributions of urban forest LST should be similar to those of ecological factors and can be represented quantitatively. Methods We used Jinjiang as a representative city in China as a case study. Population density was employed to represent anthropogenic activity. We built up a multi-source data (forest inventory, digital elevation models (DEM), population, and remote sensing imagery) on a unified urban scale to support urban forest LST influence interaction research. Through a combination of spatial statistical analysis results, multi-source spatial data, and Geogdetector model, the interaction mechanisms of urban forest LST were revealed. Results Although different ecological factors have different influences on forest LST, in two periods with different hot spots and cold spots, the patch area and dominant tree species were the main factors contributing to LST clustering in urban forests. The interaction between anthropogenic activity and multiple ecological factors increased LST in urban forest stands, linearly and nonlinearly. Strong interactions between elevation and dominant species were generally observed and were prevalent in either hot or cold spots areas in different years. Conclusions In conclusion, a combination of spatial statistics and GeogDetector models should be effective for quantitatively evaluating interactive relationships among ecological factors, anthropogenic activity and LST.

The Development of GIS Educational Resources Sharing among Central Taiwan Universities

NASA Astrophysics Data System (ADS)

Chou, T.-Y.; Yeh, M.-L.; Lai, Y.-C.

2011-09-01

Using GIS in the classroom enhance students' computer skills and explore the range of knowledge. The paper highlights GIS integration on e-learning platform and introduces a variety of abundant educational resources. This research project will demonstrate tools for e-learning environment and delivers some case studies for learning interaction from Central Taiwan Universities. Feng Chia University (FCU) obtained a remarkable academic project subsidized by Ministry of Education and developed e-learning platform for excellence in teaching/learning programs among Central Taiwan's universities. The aim of the project is to integrate the educational resources of 13 universities in central Taiwan. FCU is serving as the hub of Center University. To overcome the problem of distance, e-platforms have been established to create experiences with collaboration enhanced learning. The e-platforms provide coordination of web service access among the educational community and deliver GIS educational resources. Most of GIS related courses cover the development of GIS, principles of cartography, spatial data analysis and overlaying, terrain analysis, buffer analysis, 3D GIS application, Remote Sensing, GPS technology, and WebGIS, MobileGIS, ArcGIS manipulation. In each GIS case study, students have been taught to know geographic meaning, collect spatial data and then use ArcGIS software to analyze spatial data. On one of e-Learning platforms provide lesson plans and presentation slides. Students can learn Arc GIS online. As they analyze spatial data, they can connect to GIS hub to get data they need including satellite images, aerial photos, and vector data. Moreover, e-learning platforms provide solutions and resources. Different levels of image scales have been integrated into the systems. Multi-scale spatial development and analyses in Central Taiwan integrate academic research resources among CTTLRC partners. Thus, establish decision-making support mechanism in teaching and learning. Accelerate communication, cooperation and sharing among academic units

Compatible Spatial Discretizations for Partial Differential Equations

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

Arnold, Douglas, N, ed.

From May 11--15, 2004, the Institute for Mathematics and its Applications held a hot topics workshop on Compatible Spatial Discretizations for Partial Differential Equations. The numerical solution of partial differential equations (PDE) is a fundamental task in science and engineering. The goal of the workshop was to bring together a spectrum of scientists at the forefront of the research in the numerical solution of PDEs to discuss compatible spatial discretizations. We define compatible spatial discretizations as those that inherit or mimic fundamental properties of the PDE such as topology, conservation, symmetries, and positivity structures and maximum principles. A wide varietymore » of discretization methods applied across a wide range of scientific and engineering applications have been designed to or found to inherit or mimic intrinsic spatial structure and reproduce fundamental properties of the solution of the continuous PDE model at the finite dimensional level. A profusion of such methods and concepts relevant to understanding them have been developed and explored: mixed finite element methods, mimetic finite differences, support operator methods, control volume methods, discrete differential forms, Whitney forms, conservative differencing, discrete Hodge operators, discrete Helmholtz decomposition, finite integration techniques, staggered grid and dual grid methods, etc. This workshop seeks to foster communication among the diverse groups of researchers designing, applying, and studying such methods as well as researchers involved in practical solution of large scale problems that may benefit from advancements in such discretizations; to help elucidate the relations between the different methods and concepts; and to generally advance our understanding in the area of compatible spatial discretization methods for PDE. Particular points of emphasis included: + Identification of intrinsic properties of PDE models that are critical for the fidelity of numerical simulations. + Identification and design of compatible spatial discretizations of PDEs, their classification, analysis, and relations. + Relationships between different compatible spatial discretization methods and concepts which have been developed; + Impact of compatible spatial discretizations upon physical fidelity, verification and validation of simulations, especially in large-scale, multiphysics settings. + How solvers address the demands placed upon them by compatible spatial discretizations. This report provides information about the program and abstracts of all the presentations.« less

Investigation of noise properties in grating-based x-ray phase tomography with reverse projection method

NASA Astrophysics Data System (ADS)

Bao, Yuan; Wang, Yan; Gao, Kun; Wang, Zhi-Li; Zhu, Pei-Ping; Wu, Zi-Yu

2015-10-01

The relationship between noise variance and spatial resolution in grating-based x-ray phase computed tomography (PCT) imaging is investigated with reverse projection extraction method, and the noise variances of the reconstructed absorption coefficient and refractive index decrement are compared. For the differential phase contrast method, the noise variance in the differential projection images follows the same inverse-square law with spatial resolution as in conventional absorption-based x-ray imaging projections. However, both theoretical analysis and simulations demonstrate that in PCT the noise variance of the reconstructed refractive index decrement scales with spatial resolution follows an inverse linear relationship at fixed slice thickness, while the noise variance of the reconstructed absorption coefficient conforms with the inverse cubic law. The results indicate that, for the same noise variance level, PCT imaging may enable higher spatial resolution than conventional absorption computed tomography (ACT), while ACT benefits more from degraded spatial resolution. This could be a useful guidance in imaging the inner structure of the sample in higher spatial resolution. Project supported by the National Basic Research Program of China (Grant No. 2012CB825800), the Science Fund for Creative Research Groups, the Knowledge Innovation Program of the Chinese Academy of Sciences (Grant Nos. KJCX2-YW-N42 and Y4545320Y2), the National Natural Science Foundation of China (Grant Nos. 11475170, 11205157, 11305173, 11205189, 11375225, 11321503, 11179004, and U1332109).

Using time to investigate space: a review of tactile temporal order judgments as a window onto spatial processing in touch

PubMed Central

Heed, Tobias; Azañón, Elena

2014-01-01

To respond to a touch, it is often necessary to localize it in space, and not just on the skin. The computation of this external spatial location involves the integration of somatosensation with visual and proprioceptive information about current body posture. In the past years, the study of touch localization has received substantial attention and has become a central topic in the research field of multisensory integration. In this review, we will explore important findings from this research, zooming in on one specific experimental paradigm, the temporal order judgment (TOJ) task, which has proven particularly fruitful for the investigation of tactile spatial processing. In a typical TOJ task participants perform non-speeded judgments about the order of two tactile stimuli presented in rapid succession to different skin sites. This task could be solved without relying on external spatial coordinates. However, postural manipulations affect TOJ performance, indicating that external coordinates are in fact computed automatically. We show that this makes the TOJ task a reliable indicator of spatial remapping, and provide an overview over the versatile analysis options for TOJ. We introduce current theories of TOJ and touch localization, and then relate TOJ to behavioral and electrophysiological evidence from other paradigms, probing the benefit of TOJ for the study of spatial processing as well as related topics such as multisensory plasticity, body processing, and pain. PMID:24596561

Spatial cluster for clustering the influence factor of birth and death child in Bogor Regency, West Java

NASA Astrophysics Data System (ADS)

Bekti, Rokhana Dwi; Rachmawati, Ro'fah

2014-03-01

The number of birth and death child is the benchmarks to determine and monitor the health and welfare in Indonesia. It can be used to identify groups of people who have a high mortality risk. Identifying group is important to compare the characteristics of human that have high and low risk. These characteristics can be seen from the factors that influenced it. Furthermore, there are factors which influence of birth and death child, such us economic, health facility, education, and others. The influence factors of every individual are different, but there are similarities some individuals which live close together or in the close locations. It means there was spatial effect. To identify group in this research, clustering is done by spatial cluster method, which is view to considering the influence of the location or the relationship between locations. One of spatial cluster method is Spatial 'K'luster Analysis by Tree Edge Removal (SKATER). The research was conducted in Bogor Regency, West Java. The goal was to get a cluster of districts based on the factors that influence birth and death child. SKATER build four number of cluster respectively consists of 26, 7, 2, and 5 districts. SKATER has good performance for clustering which include spatial effect. If it compare by other cluster method, Kmeans has good performance by MANOVA test.

A NASA/University Joint Venture in Space Science (JOVE)

NASA Technical Reports Server (NTRS)

Vaughn, Danny M.

1997-01-01

Several papers have been given to national level meeting and a paper has been published in an international journal. Several additional papers have been co-author by students. The initial research project on the Atchafalaya Delta seems to have died in part due to a transfer of the NASA colleague to another location and subsequent reassigment to another job title. I have continued to include credit to NASA for many of my papers presented and published: A major debris flow along the Wasatch front in Northern Ogden; Spatial and volumetric changes in the Atchafalaya delta, Louisiana; An analysis of prehistoric Greenstone artifact in northern Alabama; An assessment of surfacing algorithm; Analysis of georeferencing algorithms to assess spatial accuracy.

Modality-specificity of Selective Attention Networks

PubMed Central

Stewart, Hannah J.; Amitay, Sygal

2015-01-01

Objective: To establish the modality specificity and generality of selective attention networks. Method: Forty-eight young adults completed a battery of four auditory and visual selective attention tests based upon the Attention Network framework: the visual and auditory Attention Network Tests (vANT, aANT), the Test of Everyday Attention (TEA), and the Test of Attention in Listening (TAiL). These provided independent measures for auditory and visual alerting, orienting, and conflict resolution networks. The measures were subjected to an exploratory factor analysis to assess underlying attention constructs. Results: The analysis yielded a four-component solution. The first component comprised of a range of measures from the TEA and was labeled “general attention.” The third component was labeled “auditory attention,” as it only contained measures from the TAiL using pitch as the attended stimulus feature. The second and fourth components were labeled as “spatial orienting” and “spatial conflict,” respectively—they were comprised of orienting and conflict resolution measures from the vANT, aANT, and TAiL attend-location task—all tasks based upon spatial judgments (e.g., the direction of a target arrow or sound location). Conclusions: These results do not support our a-priori hypothesis that attention networks are either modality specific or supramodal. Auditory attention separated into selectively attending to spatial and non-spatial features, with the auditory spatial attention loading onto the same factor as visual spatial attention, suggesting spatial attention is supramodal. However, since our study did not include a non-spatial measure of visual attention, further research will be required to ascertain whether non-spatial attention is modality-specific. PMID:26635709

Application of GIS in public health in India: A literature-based review, analysis, and recommendations.

PubMed

Ruiz, Marilyn O'Hara; Sharma, Arun Kumar

2016-01-01

The implementation of geospatial technologies and methods for improving health has become widespread in many nations, but India's adoption of these approaches has been fairly slow. With a large population, ongoing public health challenges, and a growing economy with an emphasis on innovative technologies, the adoption of spatial approaches to disease surveillance, spatial epidemiology, and implementation of health policies in India has great potential for both success and efficacy. Through our evaluation of scientific papers selected through a structured key phrase review of the National Center for Biotechnology Information on the database PubMed, we found that current spatial approaches to health research in India are fairly descriptive in nature, but the use of more complex models and statistics is increasing. The institutional home of the authors is skewed regionally, with Delhi and South India more likely to show evidence of use. The need for scientists engaged in spatial health analysis to first digitize basic data, such as maps of road networks, hydrological features, and land use, is a strong impediment to efficiency, and their work would certainly advance more quickly without this requirement.

An effective assessment protocol for continuous geospatial datasets of forest characteristics using USFS Forest Inventory and Analysis (FIA) data

Treesearch

Rachel Riemann; Barry Tyler Wilson; Andrew Lister; Sarah Parks

2010-01-01

Geospatial datasets of forest characteristics are modeled representations of real populations on the ground. The continuous spatial character of such datasets provides an incredible source of information at the landscape level for ecosystem research, policy analysis, and planning applications, all of which are critical for addressing current challenges related to...

Modeling spatial variation in avian survival and residency probabilities

USGS Publications Warehouse

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

2010-01-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2002-12-01

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

Spatial and Temporal Dust Source Variability in Northern China Identified Using Advanced Remote Sensing Analysis

NASA Technical Reports Server (NTRS)

Taramelli, A.; Pasqui, M.; Barbour, J.; Kirschbaum, D.; Bottai, L.; Busillo, C.; Calastrini, F.; Guarnieri, F.; Small, C.

2013-01-01

The aim of this research is to provide a detailed characterization of spatial patterns and temporal trends in the regional and local dust source areas within the desert of the Alashan Prefecture (Inner Mongolia, China). This problem was approached through multi-scale remote sensing analysis of vegetation changes. The primary requirements for this regional analysis are high spatial and spectral resolution data, accurate spectral calibration and good temporal resolution with a suitable temporal baseline. Landsat analysis and field validation along with the low spatial resolution classifications from MODIS and AVHRR are combined to provide a reliable characterization of the different potential dust-producing sources. The representation of intra-annual and inter-annual Normalized Difference Vegetation Index (NDVI) trend to assess land cover discrimination for mapping potential dust source using MODIS and AVHRR at larger scale is enhanced by Landsat Spectral Mixing Analysis (SMA). The combined methodology is to determine the extent to which Landsat can distinguish important soils types in order to better understand how soil reflectance behaves at seasonal and inter-annual timescales. As a final result mapping soil surface properties using SMA is representative of responses of different land and soil cover previously identified by NDVI trend. The results could be used in dust emission models even if they are not reflecting aggregate formation, soil stability or particle coatings showing to be critical for accurately represent dust source over different regional and local emitting areas.

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.

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

PubMed

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

2015-01-01

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

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

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.

Effect of spatial averaging on multifractal properties of meteorological time series

NASA Astrophysics Data System (ADS)

Hoffmann, Holger; Baranowski, Piotr; Krzyszczak, Jaromir; Zubik, Monika

2016-04-01

Introduction The process-based models for large-scale simulations require input of agro-meteorological quantities that are often in the form of time series of coarse spatial resolution. Therefore, the knowledge about their scaling properties is fundamental for transferring locally measured fluctuations to larger scales and vice-versa. However, the scaling analysis of these quantities is complicated due to the presence of localized trends and non-stationarities. Here we assess how spatially aggregating meteorological data to coarser resolutions affects the data's temporal scaling properties. While it is known that spatial aggregation may affect spatial data properties (Hoffmann et al., 2015), it is unknown how it affects temporal data properties. Therefore, the objective of this study was to characterize the aggregation effect (AE) with regard to both temporal and spatial input data properties considering scaling properties (i.e. statistical self-similarity) of the chosen agro-meteorological time series through multifractal detrended fluctuation analysis (MFDFA). Materials and Methods Time series coming from years 1982-2011 were spatially averaged from 1 to 10, 25, 50 and 100 km resolution to assess the impact of spatial aggregation. Daily minimum, mean and maximum air temperature (2 m), precipitation, global radiation, wind speed and relative humidity (Zhao et al., 2015) were used. To reveal the multifractal structure of the time series, we used the procedure described in Baranowski et al. (2015). The diversity of the studied multifractals was evaluated by the parameters of time series spectra. In order to analyse differences in multifractal properties to 1 km resolution grids, data of coarser resolutions was disaggregated to 1 km. Results and Conclusions Analysing the spatial averaging on multifractal properties we observed that spatial patterns of the multifractal spectrum (MS) of all meteorological variables differed from 1 km grids and MS-parameters were biased by -29.1 % (precipitation; width of MS) up to >4 % (min. Temperature, Radiation; asymmetry of MS). Also, the spatial variability of MS parameters was strongly affected at the highest aggregation (100 km). Obtained results confirm that spatial data aggregation may strongly affect temporal scaling properties. This should be taken into account when upscaling for large-scale studies. Acknowledgements The study was conducted within FACCE MACSUR. Please see Baranowski et al. (2015) for details on funding. References Baranowski, P., Krzyszczak, J., Sławiński, C. et al. (2015). Climate Research 65, 39-52. Hoffman, H., G. Zhao, L.G.J. Van Bussel et al. (2015). Climate Research 65, 53-69. Zhao, G., Siebert, S., Rezaei E. et al. (2015). Agricultural and Forest Meteorology 200, 156-171.

COMPOSITE SAMPLING FOR SOIL VOC ANALYSIS

EPA Science Inventory

Data published by numerous researchers over the last decade demonstrate that there is a high degree of spatial variability in the measurement of volatile organic compounds (VOCs) in soil at contaminated waste sites. This phenomenon is confounded by the use of a small sample aliqu...

EFFECTS OF CHANGING SPATIAL EXTENT ON LANDSCAPE PATTERN ANALYSIS. (R827676)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

TOWARD AN ACCURATE ANALYSIS OF RANGE QUERIES ON SPATIAL DATA. (R825195)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

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 ...

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

PubMed Central

Ghosh, Debarchana (Debs); Guha, Rajarshi

2014-01-01

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

Multiscale Spatial Assessment of Determinant Factors of Land Use Change: Study at Urban Area of Yogyakarta

NASA Astrophysics Data System (ADS)

Susilo, Bowo

2017-12-01

Studies of land use change have been undertaken by different researchers using various methods. Among those methods, modelling is widely utilized. Modelling land use change required several components remarked as model variables. Those represent any conditions or factors which considered relevant or have some degree of correlation to the changes of land use. Variables which have significant correlation to land use change are referred as determinant factors or driving forces. Those factors as well as changes of land use are distributed across space and therefore referred as spatial determinant factors. The main objective of the research was to examine land use change and its determinant factors. Area and location of land use change were analysed based on three different years of land use maps, which are 1993, 2000 and 2007. Spatial and temporal analysis were performed which emphasize to the influence of scale to both of analysis’s. Urban area of Yogyakarta was selected as study area. Study area covered three different districts (kabupaten), involving 20 sub districts and totally consists of 74 villages. Result of this study shows that during 14 years periods (1993 to 2007), there were about 1,460 hectares of land use change had been taken place. Dominant type of land use change is agricultural to residential. The uses of different spatial and temporal scale in analysis were able to reveal different factors related to land use change. In general, factors influencing the quantities of land use change in the study area were population growth and the availability of land. The use of data with different spatial resolution can reveal the presence of various factors associated with the location of the change. Locations of land use change were influenced or determined by accessibility factors.

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

PubMed

Ghosh, Debarchana Debs; Guha, Rajarshi

2013-01-01

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

A comparative analysis of the Global Land Cover 2000 and MODIS land cover data sets

USGS Publications Warehouse

Giri, C.; Zhu, Z.; Reed, B.

2005-01-01

Accurate and up-to-date global land cover data sets are necessary for various global change research studies including climate change, biodiversity conservation, ecosystem assessment, and environmental modeling. In recent years, substantial advancement has been achieved in generating such data products. Yet, we are far from producing geospatially consistent high-quality data at an operational level. We compared the recently available Global Land Cover 2000 (GLC-2000) and MODerate resolution Imaging Spectrometer (MODIS) global land cover data to evaluate the similarities and differences in methodologies and results, and to identify areas of spatial agreement and disagreement. These two global land cover data sets were prepared using different data sources, classification systems, and methodologies, but using the same spatial resolution (i.e., 1 km) satellite data. Our analysis shows a general agreement at the class aggregate level except for savannas/shrublands, and wetlands. The disagreement, however, increases when comparing detailed land cover classes. Similarly, percent agreement between the two data sets was found to be highly variable among biomes. The identified areas of spatial agreement and disagreement will be useful for both data producers and users. Data producers may use the areas of spatial agreement for training area selection and pay special attention to areas of disagreement for further improvement in future land cover characterization and mapping. Users can conveniently use the findings in the areas of agreement, whereas users might need to verify the informaiton in the areas of disagreement with the help of secondary information. Learning from past experience and building on the existing infrastructure (e.g., regional networks), further research is necessary to (1) reduce ambiguity in land cover definitions, (2) increase availability of improved spatial, spectral, radiometric, and geometric resolution satellite data, and (3) develop advanced classification algorithms.

Determination of the complex refractive index segments of turbid sample with multispectral spatially modulated structured light and models approximation

NASA Astrophysics Data System (ADS)

Meitav, Omri; Shaul, Oren; Abookasis, David

2017-09-01

Spectral data enabling the derivation of a biological tissue sample's complex refractive index (CRI) can provide a range of valuable information in the clinical and research contexts. Specifically, changes in the CRI reflect alterations in tissue morphology and chemical composition, enabling its use as an optical marker during diagnosis and treatment. In the present work, we report a method for estimating the real and imaginary parts of the CRI of a biological sample using Kramers-Kronig (KK) relations in the spatial frequency domain. In this method, phase-shifted sinusoidal patterns at single high spatial frequency are serially projected onto the sample surface at different near-infrared wavelengths while a camera mounted normal to the sample surface acquires the reflected diffuse light. In the offline analysis pipeline, recorded images at each wavelength are converted to spatial phase maps using KK analysis and are then calibrated against phase-models derived from diffusion approximation. The amplitude of the reflected light, together with phase data, is then introduced into Fresnel equations to resolve both real and imaginary segments of the CRI at each wavelength. The technique was validated in tissue-mimicking phantoms with known optical parameters and in mouse models of ischemic injury and heat stress. Experimental data obtained indicate variations in the CRI among brain tissue suffering from injury. CRI fluctuations correlated with alterations in the scattering and absorption coefficients of the injured tissue are demonstrated. This technique for deriving dynamic changes in the CRI of tissue may be further developed as a clinical diagnostic tool and for biomedical research applications. To the best of our knowledge, this is the first report of the estimation of the spectral CRI of a mouse head following injury obtained in the spatial frequency domain.

MPATHav: A software prototype for multiobjective routing in transportation risk assessment

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

Ganter, J.H.; Smith, J.D.

Most routing problems depend on several important variables: transport distance, population exposure, accident rate, mandated roads (e.g., HM-164 regulations), and proximity to emergency response resources are typical. These variables may need to be minimized or maximized, and often are weighted. `Objectives` to be satisfied by the analysis are thus created. The resulting problems can be approached by combining spatial analysis techniques from geographic information systems (GIS) with multiobjective analysis techniques from the field of operations research (OR); we call this hybrid multiobjective spatial analysis` (MOSA). MOSA can be used to discover, display, and compare a range of solutions that satisfymore » a set of objectives to varying degrees. For instance, a suite of solutions may include: one solution that provides short transport distances, but at a cost of high exposure; another solution that provides low exposure, but long distances; and a range of solutions between these two extremes.« less

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.

GIS-based Landing-Site Analysis and Passive Decision Support

NASA Astrophysics Data System (ADS)

van Gasselt, Stephan; Nass, Andrea

2016-04-01

The increase of surface coverage and the availability and accessibility of planetary data allow researchers and engineers to remotely perform detailed studies on surface processes and properties, in particular on objects such as Mars and the Moon for which Terabytes of multi-temporal data at multiple spatial resolution levels have become available during the last 15 years. Orbiters, rovers and landers have been returning information and insights into the surface evolution of the terrestrial planets in unprecedented detail. While rover- and lander-based analyses are one major research aim to obtain ground truth, resource exploration or even potential establishment of bases using autonomous platforms are others and they require detailed investigation of settings in order to identify spots on the surface that are suitable for spacecraft to land and operate safely and over a long period of time. What has been done using hardcopy material in the past is today being carried by using either in-house developments or off-the-shelf spatial information system technology which allows to manage, integrate and analyse data as well as visualize and create user-defined reports for performing assessments. Usually, such analyses can be broken down (manually) by considering scientific wishes, engineering boundary conditions, potential hazards and various tertiary constraints. We here (1) review standard tasks of landing site analyses, (2) discuss issues inherently related to the analysis using integrated spatial analysis systems and (3) demonstrate a modular analysis framework for integration of data and for the evaluation of results from individual tasks in order to support decisions for landing-site selection.

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

NASA Astrophysics Data System (ADS)

Munawar, Iqra

2016-07-01

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

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data

PubMed Central

Broekhuis, Femke; Gopalaswamy, Arjun M.

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed ‘hotspots’ of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species. PMID:27135614

Counting Cats: Spatially Explicit Population Estimates of Cheetah (Acinonyx jubatus) Using Unstructured Sampling Data.

PubMed

Broekhuis, Femke; Gopalaswamy, Arjun M

2016-01-01

Many ecological theories and species conservation programmes rely on accurate estimates of population density. Accurate density estimation, especially for species facing rapid declines, requires the application of rigorous field and analytical methods. However, obtaining accurate density estimates of carnivores can be challenging as carnivores naturally exist at relatively low densities and are often elusive and wide-ranging. In this study, we employ an unstructured spatial sampling field design along with a Bayesian sex-specific spatially explicit capture-recapture (SECR) analysis, to provide the first rigorous population density estimates of cheetahs (Acinonyx jubatus) in the Maasai Mara, Kenya. We estimate adult cheetah density to be between 1.28 ± 0.315 and 1.34 ± 0.337 individuals/100km2 across four candidate models specified in our analysis. Our spatially explicit approach revealed 'hotspots' of cheetah density, highlighting that cheetah are distributed heterogeneously across the landscape. The SECR models incorporated a movement range parameter which indicated that male cheetah moved four times as much as females, possibly because female movement was restricted by their reproductive status and/or the spatial distribution of prey. We show that SECR can be used for spatially unstructured data to successfully characterise the spatial distribution of a low density species and also estimate population density when sample size is small. Our sampling and modelling framework will help determine spatial and temporal variation in cheetah densities, providing a foundation for their conservation and management. Based on our results we encourage other researchers to adopt a similar approach in estimating densities of individually recognisable species.

Joint Multifractal Analysis of penetration resistance variability in an olive orchard.

NASA Astrophysics Data System (ADS)

Lopez-Herrera, Juan; Herrero-Tejedor, Tomas; Saa-Requejo, Antonio; Villeta, Maria; Tarquis, Ana M.

2016-04-01

Spatial variability of soil properties is relevant for identifying those zones with physical degradation. We used descriptive statistics and multifractal analysis for characterizing the spatial patterns of soil penetrometer resistance (PR) distributions and compare them at different soil depths and soil water content to investigate the tillage effect in soil compactation. The study was conducted on an Inceptisol dedicated to olive orchard for the last 70 years. Two parallel transects of 64 m were selected as different soil management plots, conventional tillage (CT) and no tillage (NT). Penetrometer resistance readings were carried out at 50 cm intervals within the first 20 cm of soil depth (López de Herrera et al., 2015a). Two way ANOVA highlighted that tillage system, soil depth and their interaction are statistically significant to explain the variance of PR data. The comparison of CT and NT results at different depths showed that there are significant differences deeper than 10 cm but not in the first two soil layers. The scaling properties of each PR profile was characterized by τ(q) function, calculated in the range of moment orders (q) between -5 and +5 taken at 0.5 lag increments. Several parameters were calculated from this to establish different comparisons (López de Herrera et al., 2015b). While the multifractal analysis characterizes the distribution of a single variable along its spatial support, the joint multifractal analysis can be used to characterize the joint distribution of two or more variables along a common spatial support (Kravchenko et al., 2000; Zeleke and Si, 2004). This type of analysis was performed to study the scaling properties of the joint distribution of PR at different depths. The results showed that this type of analysis added valuable information to describe the spatial arrangement of depth-dependent penetrometer data sets in all the soil layers. References Kravchenko AN, Bullock DG, Boast CW (2000) Joint multifractal analysis of crop yield and terrain slope. Agro. j. 92: 1279-1290. López de Herrera, J., Tomas Herrero Tejedor, Antonio Saa-Requejo and Ana M. Tarquis (2015a) Influence of tillage in soil penetration resistance variability in an olive orchard. Geophysical Research Abstracts, 17, EGU2015-15425. López de Herrera, J., Tomás Herrero Tejedor, Antonio Saa-Requejo, A.M. Tarquis. Influence of tillage in soil penetration resistance variability in an olive orchard. Soil Research, accepted, 2015b. doi: SR15046 Zeleke TB, Si BC (2004) Scaling properties of topographic indices and crop yield: Multifractal and joint multifractal approaches. Agro. j. 96: 1082-1090.

a Multidisciplinary Analytical Framework for Studying Active Mobility Patterns

NASA Astrophysics Data System (ADS)

Orellana, D.; Hermida, C.; Osorio, P.

2016-06-01

Intermediate cities are urged to change and adapt their mobility systems from a high energy-demanding motorized model to a sustainable low-motorized model. In order to accomplish such a model, city administrations need to better understand active mobility patterns and their links to socio-demographic and cultural aspects of the population. During the last decade, researchers have demonstrated the potential of geo-location technologies and mobile devices to gather massive amounts of data for mobility studies. However, the analysis and interpretation of this data has been carried out by specialized research groups with relatively narrow approaches from different disciplines. Consequently, broader questions remain less explored, mainly those relating to spatial behaviour of individuals and populations with their geographic environment and the motivations and perceptions shaping such behaviour. Understanding sustainable mobility and exploring new research paths require an interdisciplinary approach given the complex nature of mobility systems and their social, economic and environmental impacts. Here, we introduce the elements for a multidisciplinary analytical framework for studying active mobility patterns comprised of three components: a) Methodological, b) Behavioural, and c) Perceptual. We demonstrate the applicability of the framework by analysing mobility patterns of cyclists and pedestrians in an intermediate city integrating a range of techniques, including: GPS tracking, spatial analysis, auto-ethnography, and perceptual mapping. The results demonstrated the existence of non-evident spatial behaviours and how perceptual features affect mobility. This knowledge is useful for developing policies and practices for sustainable mobility planning.

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

PubMed

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

2016-07-01

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

Should Data Frameworks be Inherently Multiscalar? A Use Case of the Living Atlas of the World

NASA Astrophysics Data System (ADS)

Wright, D. J.

2015-12-01

In addition to an individual research project, many researchers are involved in at least one major partnership, perhaps one ocean observatory, or one collaborative. The accompanying data framework may be focused on a subdiscipline of oceanography (i.e., marine geology and geophysics, physical oceanography, marine ecology, etc.) or particular study region. The data framework obviously exists to support research, but also collaboration in data collection, spatial analysis, visualization, and communication of the science to multiple audience. These interactions likely take place at multiple scales: the scale of the individual researcher, of small workgroups within a lab, or of inter-organizational collaboration. There are also frameworks that cut horizontally across discipline and region, connecting to broader national or global initiatives such as NSF EarthCube, other NSF-funded Research Coordination Networks, GEOSS, or ODIP. The Living Atlas of the World is presented as a use case of a data framework seeking to cut effectively across multiple spatial and temporal scales. The Living Atlas was first created in 2014 to make authoritative geographic information accessible via hosted cloud services so that users could more quickly address scientific and societal problems and decisions at spatial scales ranging from a small study area the entire globe, while using a range of interactive map functions to tell engaging narratives along the way (aka "story maps"). What began as a way to build trusted, authoritative, and freely available *basemaps* from data contributed online by the GIS community, has grown to a larger program extending far beyond basemap layers to satellite imagery, bathymetry, water column layers, and hydrology, as well elevation, human population, and 3D web scenes. The Living Atlas is continually under construction with new efforts that now extend beyond just the reading and serving of dataset, to the provisioning of spatial analysis on these *data services* in the cloud, as well as the crosswalking and sharing of workflows and use cases, additional apps for mobile, web, and desktop, community-building events where people gather face-to-face, and close interlinkages to other platforms such as ODIP and NSF EarthCube.

The malleability of spatial skills: a meta-analysis of training studies.

PubMed

Uttal, David H; Meadow, Nathaniel G; Tipton, Elizabeth; Hand, Linda L; Alden, Alison R; Warren, Christopher; Newcombe, Nora S

2013-03-01

Having good spatial skills strongly predicts achievement and attainment in science, technology, engineering, and mathematics fields (e.g., Shea, Lubinski, & Benbow, 2001; Wai, Lubinski, & Benbow, 2009). Improving spatial skills is therefore of both theoretical and practical importance. To determine whether and to what extent training and experience can improve these skills, we meta-analyzed 217 research studies investigating the magnitude, moderators, durability, and generalizability of training on spatial skills. After eliminating outliers, the average effect size (Hedges's g) for training relative to control was 0.47 (SE = 0.04). Training effects were stable and were not affected by delays between training and posttesting. Training also transferred to other spatial tasks that were not directly trained. We analyzed the effects of several moderators, including the presence and type of control groups, sex, age, and type of training. Additionally, we included a theoretically motivated typology of spatial skills that emphasizes 2 dimensions: intrinsic versus extrinsic and static versus dynamic (Newcombe & Shipley, in press). Finally, we consider the potential educational and policy implications of directly training spatial skills. Considered together, the results suggest that spatially enriched education could pay substantial dividends in increasing participation in mathematics, science, and engineering. © 2013 American Psychological Association

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.

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...

New data for relating land use and urban form to private passenger vehicle miles.

DOT National Transportation Integrated Search

2013-08-01

This research project developed the most extensive and spatially detailed analysis of : annual vehicle miles traveled (VMT) by type of vehicle, place of residence, and land use : pattern. We combined a unique Massachusetts State dataset of annual odo...

Investigations in Mathematics Education. Volume 16, Number 2.

ERIC Educational Resources Information Center

Investigations in Mathematics Education, 1983

1983-01-01

Abstracts of 11 mathematics education research studies are provided. Each abstract is accompanied by the abstractor's analysis of or comments about the study. Studies reported include: "The Importance of Spatial Visualization and Cognitive Development for Geometry Learning in Preservice Elementary Teachers"; "Classroom Ratio of High…

Spatial and temporal variability of soil temperature, moisture and surface soil properties

NASA Technical Reports Server (NTRS)

Hajek, B. F.; Dane, J. H.

1993-01-01

The overall objectives of this research were to: (l) Relate in-situ measured soil-water content and temperature profiles to remotely sensed surface soil-water and temperature conditions; to model simultaneous heat and water movement for spatially and temporally changing soil conditions; (2) Determine the spatial and temporal variability of surface soil properties affecting emissivity, reflectance, and material and energy flux across the soil surface. This will include physical, chemical, and mineralogical characteristics of primary soil components and aggregate systems; and (3) Develop surface soil classes of naturally occurring and distributed soil property assemblages and group classes to be tested with respect to water content, emissivity and reflectivity. This document is a report of studies conducted during the period funded by NASA grants. The project was designed to be conducted over a five year period. Since funding was discontinued after three years, some of the research started was not completed. Additional publications are planned whenever funding can be obtained to finalize data analysis for both the arid and humid locations.

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

USGS Publications Warehouse

Lewison, R.L.; Carter, J.

2004-01-01

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

Monitoring the transformation of Yogyakarta’s urban form using remote sensing and Geographic Information System

NASA Astrophysics Data System (ADS)

Rozano, B.; Yan, W.

2018-04-01

Urban form transformation can be seen as the results of urbanization spatially, where the land changed into an urbanized one. Monitoring its changes, however, require many human and financial resources. Accordingly, this research aims to identify urban form transformation using GIS/remote sensing and its spatial implications to the peri-urban area. In order to analyze the land cover changes, this research uses multispectral images from 1990-2016 for built-up extraction using New Built Up Index (NBUI) analysis and population data 1996-2015 combined with primary data from the respondents and key informants. Based on the analysis, it is seen that the compacted Yogyakarta Urban Area scattered predominantly to the Northern part of its periphery with the increase of urban area from 21.19% in 1990 to 50.91% in 2017. While this urbanization is an on-going process, the population of urban core showed a de-concentration phenomenon in 2015, spreading to its periphery causing some negative implications to the peri-urban area.

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

PubMed

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

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.

Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing Observations

PubMed Central

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

2014-01-01

Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760

Collaborative Research with Chinese, Indian, Filipino and North European Research Organizations on Infectious Disease Epidemics.

PubMed

Sumi, Ayako; Kobayashi, Nobumichi

2017-01-01

In this report, we present a short review of applications of time series analysis, which consists of spectral analysis based on the maximum entropy method in the frequency domain and the least squares method in the time domain, to the incidence data of infectious diseases. This report consists of three parts. First, we present our results obtained by collaborative research on infectious disease epidemics with Chinese, Indian, Filipino and North European research organizations. Second, we present the results obtained with the Japanese infectious disease surveillance data and the time series numerically generated from a mathematical model, called the susceptible/exposed/infectious/recovered (SEIR) model. Third, we present an application of the time series analysis to pathologic tissues to examine the usefulness of time series analysis for investigating the spatial pattern of pathologic tissue. It is anticipated that time series analysis will become a useful tool for investigating not only infectious disease surveillance data but also immunological and genetic tests.

Detection of spatial hot spots and variation for the neon flying squid Ommastrephes bartramii resources in the northwest Pacific Ocean

NASA Astrophysics Data System (ADS)

Feng, Yongjiu; Chen, Xinjun; Liu, Yan

2017-07-01

With the increasing effects of global climate change and fishing activities, the spatial distribution of the neon flying squid ( Ommastrephes bartramii) is changing in the traditional fishing ground of 150°-160°E and 38°-45°N in the northwest Pacific Ocean. This research aims to identify the spatial hot and cold spots (i.e. spatial clusters) of O. bartramii to reveal its spatial structure using commercial fishery data from 2007 to 2010 collected by Chinese mainland squid-jigging fleets. A relatively strongly-clustered distribution for O. bartramii was observed using an exploratory spatial data analysis (ESDA) method. The results show two hot spots and one cold spot in 2007 while only one hot and one cold spots were identified each year from 2008 to 2010. The hot and cold spots in 2007 occupied 8.2% and 5.6% of the study area, respectively; these percentages for hot and cold spot areas were 5.8% and 3.1% in 2008, 10.2% and 2.9% in 2009, and 16.4% and 11.9% in 2010, respectively. Nearly half (>45%) of the squid from 2007 to 2009 reported by Chinese fleets were caught in hot spot areas while this percentage reached its peak at 68.8% in 2010, indicating that the hot spot areas are central fishing grounds. A further change analysis shows the area centered at 156°E/43.5°N was persistent as a hot spot over the whole period from 2007 to 2010. Furthermore, the hot spots were mainly identified in areas with sea surface temperature (SST) in the range of 15-20°C around warm Kuroshio Currents as well as with the chlorophyll- a (chl- a) concentration above 0.3 mg/m3. The outcome of this research improves our understanding of spatiotemporal hotspots and its variation for O. bartramii and is useful for sustainable exploitation, assessment, and management of this squid.

75 years of dryland science: Trends and gaps in arid ecology literature

PubMed Central

Dickman, Chris R.; Wardle, Glenda M.

2017-01-01

Growth in the publication of scientific articles is occurring at an exponential rate, prompting a growing need to synthesise information in a timely manner to combat urgent environmental problems and guide future research. Here, we undertake a topic analysis of dryland literature over the last 75 years (8218 articles) to identify areas in arid ecology that are well studied and topics that are emerging. Four topics—wetlands, mammal ecology, litter decomposition and spatial modelling, were identified as ‘hot topics’ that showed higher than average growth in publications from 1940 to 2015. Five topics—remote sensing, climate, habitat and spatial, agriculture and soils-microbes, were identified as ‘cold topics’, with lower than average growth over the survey period, but higher than average numbers of publications. Topics in arid ecology clustered into seven broad groups on word-based similarity. These groups ranged from mammal ecology and population genetics, broad-scale management and ecosystem modelling, plant ecology, agriculture and ecophysiology, to populations and paleoclimate. These patterns may reflect trends in the field of ecology more broadly. We also identified two broad research gaps in arid ecology: population genetics, and habitat and spatial research. Collaborations between population genetics and ecologists and investigations of ecological processes across spatial scales would contribute profitably to the advancement of arid ecology and to ecology more broadly. PMID:28384186

A Dynamic Integration Method for Borderland Database using OSM data

NASA Astrophysics Data System (ADS)

Zhou, X.-G.; Jiang, Y.; Zhou, K.-X.; Zeng, L.

2013-11-01

Spatial data is the fundamental of borderland analysis of the geography, natural resources, demography, politics, economy, and culture. As the spatial region used in borderland researching usually covers several neighboring countries' borderland regions, the data is difficult to achieve by one research institution or government. VGI has been proven to be a very successful means of acquiring timely and detailed global spatial data at very low cost. Therefore VGI will be one reasonable source of borderland spatial data. OpenStreetMap (OSM) has been known as the most successful VGI resource. But OSM data model is far different from the traditional authoritative geographic information. Thus the OSM data needs to be converted to the scientist customized data model. With the real world changing fast, the converted data needs to be updated. Therefore, a dynamic integration method for borderland data is presented in this paper. In this method, a machine study mechanism is used to convert the OSM data model to the user data model; a method used to select the changed objects in the researching area over a given period from OSM whole world daily diff file is presented, the change-only information file with designed form is produced automatically. Based on the rules and algorithms mentioned above, we enabled the automatic (or semiautomatic) integration and updating of the borderland database by programming. The developed system was intensively tested.

Transforming Spatial Reasoning Skills in the Upper-Level Undergraduate Geoscience Classroom Through Curricular Materials Informed by 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.

2014-12-01

Spatial visualization is an essential skill in the STEM disciplines, including the geosciences. 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 be unable to understand fundamental concepts and to solve geological problems with a spatial component. However, spatial thinking skills are malleable. As a group of geoscience faculty members and cognitive psychologists, we have developed a set of curricular materials for Mineralogy, Sedimentology & Stratigraphy, and Structural Geology courses. These materials are designed to improve students' spatial skills, and in particular to improve students' abilities to reason about spatially complex 3D geological concepts and problems. Teaching spatial thinking in the context of discipline-based exercises has the potential to transform undergraduate STEM education by removing one significant barrier to success in the STEM disciplines. The curricular materials we have developed are based on several promising teaching strategies that have emerged from cognitive science research on spatial thinking. These strategies include predictive sketching, making visual comparisons, gesturing, and the use of analogy. We have conducted a three-year study of the efficacy of these materials in strengthening the spatial skills of students in upper-level geoscience courses at three universities. Our methodology relies on a pre- and post-test study design, with several tests of spatial thinking skills administered at the beginning and end of each semester. In 2011-2012, we used a "business as usual" approach to gather baseline data, measuring how much students' spatial thinking skills improved in response to the existing curricula. In the two subsequent years we have incorporated our new curricular materials, which can be found on the project website: http://serc.carleton.edu/spatialworkbook/activities.html Structural Geology students exposed to the new curricular materials are better able to solve some spatially challenging structural geological problems than students from the baseline year. We are continuing to analyze data from the Mineralogy and Sedimentology/Stratigraphy courses and will have completed the analysis by AGU.

Coi-wiz: An interactive computer wizard for analyzing cardiac optical signals.

PubMed

Yuan, Xiaojing; Uyanik, Ilyas; Situ, Ning; Xi, Yutao; Cheng, Jie

2009-01-01

A number of revolutionary techniques have been developed for cardiac electrophysiology research to better study the various arrhythmia mechanisms that can enhance ablating strategies for cardiac arrhythmias. Once the three-dimensional high resolution cardiac optical imaging data is acquired, it is time consuming to manually go through them and try to identify the patterns associated with various arrhythmia symptoms. In this paper, we present an interactive computer wizard that helps cardiac electrophysiology researchers to visualize and analyze the high resolution cardiac optical imaging data. The wizard provides a file interface that accommodates different file formats. A series of analysis algorithms output waveforms, activation and action potential maps after spatial and temporal filtering, velocity field and heterogeneity measure. The interactive GUI allows the researcher to identify the region of interest in both the spatial and temporal domain, thus enabling them to study different heart chamber at their choice.

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.

Temporal and spatial assessment of river surface water quality using multivariate statistical techniques: a study in Can Tho City, a Mekong Delta area, Vietnam.

PubMed

Phung, Dung; Huang, Cunrui; Rutherford, Shannon; Dwirahmadi, Febi; Chu, Cordia; Wang, Xiaoming; Nguyen, Minh; Nguyen, Nga Huy; Do, Cuong Manh; Nguyen, Trung Hieu; Dinh, Tuan Anh Diep

2015-05-01

The present study is an evaluation of temporal/spatial variations of surface water quality using multivariate statistical techniques, comprising cluster analysis (CA), principal component analysis (PCA), factor analysis (FA) and discriminant analysis (DA). Eleven water quality parameters were monitored at 38 different sites in Can Tho City, a Mekong Delta area of Vietnam from 2008 to 2012. Hierarchical cluster analysis grouped the 38 sampling sites into three clusters, representing mixed urban-rural areas, agricultural areas and industrial zone. FA/PCA resulted in three latent factors for the entire research location, three for cluster 1, four for cluster 2, and four for cluster 3 explaining 60, 60.2, 80.9, and 70% of the total variance in the respective water quality. The varifactors from FA indicated that the parameters responsible for water quality variations are related to erosion from disturbed land or inflow of effluent from sewage plants and industry, discharges from wastewater treatment plants and domestic wastewater, agricultural activities and industrial effluents, and contamination by sewage waste with faecal coliform bacteria through sewer and septic systems. Discriminant analysis (DA) revealed that nephelometric turbidity units (NTU), chemical oxygen demand (COD) and NH₃ are the discriminating parameters in space, affording 67% correct assignation in spatial analysis; pH and NO₂ are the discriminating parameters according to season, assigning approximately 60% of cases correctly. The findings suggest a possible revised sampling strategy that can reduce the number of sampling sites and the indicator parameters responsible for large variations in water quality. This study demonstrates the usefulness of multivariate statistical techniques for evaluation of temporal/spatial variations in water quality assessment and management.

Vulnerabilities of Local Healthcare Providers in Complex Emergencies: Findings from the Manipur Micro-level Insurgency Database 2008-2009.

PubMed

Sinha, Samrat; David, Siddarth; Gerdin, Martin; Roy, Nobhojit

2013-04-24

Research on healthcare delivery in zones of conflict requires sustained and systematic attention. In the context of the South Asian region, there has been an absence of research on the vulnerabilities of health care workers and institutions in areas affected by armed conflict. The paper presents a case study of the varied nature of security challenges faced by local healthcare providers in the state of Manipur in the North-eastern region of India, located in the Indo-Myanmar frontier region which has been experiencing armed violence and civil strife since the late 1960s. . The aim of this study was to assess longitudinal and spatial trends in incidents involving health care workers in Manipur during the period 2008 to 2009. We conducted a retrospective database analysis of the Manipur Micro-level Insurgency Database 2008-2009, created by using local newspaper archives to measure the overall burden of violence experienced in the state over a two year period. Publicly available press releases of armed groups and local hospitals in the state were used to supplement the quantitative data. Simple linear regression was used to assess longitudinal trends. Data was visualized with GIS-software for spatial analysis. The mean proportion of incidents involving health care workers per month was 2.7% and ranged between 0 and 6.1% (table 2). There was a significant (P=0.037) month-to-month variation in the proportion of incidents involving health care workers, as well as a upward trend of about 0.11% per month. Spatial analysis revealed different patterns depending on whether absolute, population-adjusted, or incident-adjusted frequencies served as the basis of the analysis. The paper shows a small but steady rise in violence against health workers and health institutions impeding health services in Manipur's pervasive violence. More evidence-building backed by research along with institutional obligations and commitment is essential to protect the health-systems Keywords: India, Manipur, insurgency, healthcare, security, ethnic strife.

The Use of Spatial Data Infrastructure in Environmental Management:an Example from the Spatial Planning Practice in Poland.

PubMed

Zwirowicz-Rutkowska, Agnieszka; Michalik, Anna

2016-10-01

Today's technology plays a crucial role in the effective use of environmental information. This includes geographic information systems and infrastructures. The purpose of this research is to identify the way in which the Polish spatial data infrastructure (PSDI) supports policies and activities that may have an impact on the environment in relation to one group of users, namely urban planners, and their tasks concerning environmental management. The study is based on a survey conducted in July and August, 2014. Moreover, the authors' expert knowledge gained through urban development practice and the analysis of the environmental conservation regulations and spatial planning in Poland has been used to define the scope of environmental management in both spatial planning studies and spatial data sources. The research included assessment of data availability, infrastructure usability, and its impact on decision-making process. The results showed that the PSDI is valuable because it allows for the acquisition of data on environmental monitoring, agricultural and aquaculture facilities. It also has a positive impact on decision-making processes and improves numerous planners' activities concerning both the inclusion of environmental indicators in spatial plans and the support of nature conservation and environmental management in the process of working on future land use. However, even though the infrastructure solves certain problems with data accessibility, further improvements might be proposed. The importance of the SDI in environmental management is noticeable and could be considered from many standpoints: Data, communities engaged in policy or decision-making concerning environmental issues, and data providers.

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.

Collaborating and sharing data in epilepsy research.

PubMed

Wagenaar, Joost B; Worrell, Gregory A; Ives, Zachary; Dümpelmann, Matthias; Matthias, Dümpelmann; Litt, Brian; Schulze-Bonhage, Andreas

2015-06-01

Technological advances are dramatically advancing translational research in Epilepsy. Neurophysiology, imaging, and metadata are now recorded digitally in most centers, enabling quantitative analysis. Basic and translational research opportunities to use these data are exploding, but academic and funding cultures prevent this potential from being realized. Research on epileptogenic networks, antiepileptic devices, and biomarkers could progress rapidly if collaborative efforts to digest this "big neuro data" could be organized. Higher temporal and spatial resolution data are driving the need for novel multidimensional visualization and analysis tools. Crowd-sourced science, the same that drives innovation in computer science, could easily be mobilized for these tasks, were it not for competition for funding, attribution, and lack of standard data formats and platforms. As these efforts mature, there is a great opportunity to advance Epilepsy research through data sharing and increase collaboration between the international research community.

Measurement of forest disturbance and regrowth with Landsat and forest inventory and analysis data: anticipated benefits from forest and inventory analysis' collaboration with the national aeronautics and space administration and university partners

Treesearch

Sean Healey; Gretchen Moisen; Jeff Masek; Warren Cohen; Sam Goward; < i> et al< /i>

2007-01-01

The Forest Inventory and Analysis (FIA) program has partnered with researchers from the National Aeronautics and Space Administration, the University of Maryland, and other U.S. Department of Agriculture Forest Service units to identify disturbance patterns across the United States using FIA plot data and time series of Landsat satellite images. Spatially explicit...

MTF Analysis of LANDSAT-4 Thematic Mapper

NASA Technical Reports Server (NTRS)

Schowengerdt, R.

1984-01-01

A research program to measure the LANDSAT 4 Thematic Mapper (TM) modulation transfer function (MTF) is described. Measurement of a satellite sensor's MTF requires the use of a calibrated ground target, i.e., the spatial radiance distribution of the target must be known to a resolution at least four to five times greater than that of the system under test. A small reflective mirror or a dark light linear pattern such as line or edge, and relatively high resolution underflight imagery are used to calibrate the target. A technique that utilizes an analytical model for the scene spatial frequency power spectrum will be investigated as an alternative to calibration of the scene. The test sites and analysis techniques are also described.

GoMRC Website ‘Meta-analysis Report: Land-use and submerged aquatic vegetation change in the Gulf of Mexico’

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

Judd, Chaeli; Stefansson, Emily S.; Brushnahan, Heather

2007-12-06

Over the past century, health and spatial extent of seagrasses has decreased dramatically in the Gulf of Mexico. While some of the changes can be explained by direct impacts to the seagrass beds, we hypothesize that changes in the land use in the watersheds can also be correlated with the decline of seagrasses. Through this meta-analysis, we researched historical and compared trends in seagrass populations and land use in five bays and their watersheds within the Gulf of Mexico: Mobile Bay, Perdido Bay, Tampa Bay, Charlotte Harbor, and Galveston Bay. Using both historical records and spatial datasets, we examined landmore » use and seagrass trends in these five areas.« less

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.

Does Competition Improve Public School Efficiency? A Spatial Analysis

ERIC Educational Resources Information Center

Misra, Kaustav; Grimes, Paul W.; Rogers, Kevin E.

2012-01-01

Advocates for educational reform frequently call for policies to increase competition between schools because it is argued that market forces naturally lead to greater efficiencies, including improved student learning, when schools face competition. Researchers examining this issue are confronted with difficulties in defining reasonable measures…

ENVIRONMENTAL TECHNOLOGY VERIFICATION REPORT, ENVIRONMENTAL DECISION SUPPORT SOFTWARE, UNIVERSITY OF TENNESSEE RESEARCH CORPORATION, SPATIAL ANALYSIS AND DECISION ASSISTANCE (SADA)

EPA Science Inventory

The U.S. Environmental Protection Agency (EPA) has created the Environmental Technology Verification Program (ETV) to facilitate the deployment of innovative or improved environmental technologies through performance verification and dissemination of information. The goal of the...

Transduction between worlds: using virtual and mixed reality for earth and planetary science

NASA Astrophysics Data System (ADS)

Hedley, N.; Lochhead, I.; Aagesen, S.; Lonergan, C. D.; Benoy, N.

2017-12-01

Virtual reality (VR) and augmented reality (AR) have the potential to transform the way we visualize multidimensional geospatial datasets in support of geoscience research, exploration and analysis. The beauty of virtual environments is that they can be built at any scale, users can view them at many levels of abstraction, move through them in unconventional ways, and experience spatial phenomena as if they had superpowers. Similarly, augmented reality allows you to bring the power of virtual 3D data visualizations into everyday spaces. Spliced together, these interface technologies hold incredible potential to support 21st-century geoscience. In my ongoing research, my team and I have made significant advances to connect data and virtual simulations with real geographic spaces, using virtual environments, geospatial augmented reality and mixed reality. These research efforts have yielded new capabilities to connect users with spatial data and phenomena. These innovations include: geospatial x-ray vision; flexible mixed reality; augmented 3D GIS; situated augmented reality 3D simulations of tsunamis and other phenomena interacting with real geomorphology; augmented visual analytics; and immersive GIS. These new modalities redefine the ways in which we can connect digital spaces of spatial analysis, simulation and geovisualization, with geographic spaces of data collection, fieldwork, interpretation and communication. In a way, we are talking about transduction between real and virtual worlds. Taking a mixed reality approach to this, we can link real and virtual worlds. This paper presents a selection of our 3D geovisual interface projects in terrestrial, coastal, underwater and other environments. Using rigorous applied geoscience data, analyses and simulations, our research aims to transform the novelty of virtual and augmented reality interface technologies into game-changing mixed reality geoscience.

Students’ Spatial Performance: Cognitive Style and Sex Differences

NASA Astrophysics Data System (ADS)

Hanifah, U.; Juniati, D.; Siswono, T. Y. E.

2018-01-01

This study aims at describing the students’ spatial abilities based on cognitive styles and sex differences. Spatial abilities in this study include 5 components, namely spatial perception, spatial visualization, mental rotation, spatial relations, and spatial orientation. This research is descriptive research with qualitative approach. The subjects in this research were 4 students of junior high school, there were 1 male FI, 1 male FD, 1 female FI, and 1 female FI. The results showed that there are differences in spatial abilities of the four subjects that are on the components of spatial visualization, mental rotation, and spatial relations. The differences in spatial abilities were found in methods / strategies used by each subject to solve each component problem. The differences in cognitive styles and sex suggested different choice of strategies used to solve problems. The male students imagined the figures but female students needed the media to solve the problem. Besides sex, the cognitive style differences also have an effect on solving a problem. In addition, FI students were not affected by distracting information but FD students could be affected by distracting information. This research was expected to contribute knowledge and insight to the readers, especially for math teachers in terms of the spatial ability of the students so that they can optimize their students’ spatial ability.

A New Methodology of Spatial Cross-Correlation Analysis

PubMed Central

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran’s index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson’s correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China’s urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes. PMID:25993120

A new methodology of spatial cross-correlation analysis.

PubMed

Chen, Yanguang

2015-01-01

Spatial correlation modeling comprises both spatial autocorrelation and spatial cross-correlation processes. The spatial autocorrelation theory has been well-developed. It is necessary to advance the method of spatial cross-correlation analysis to supplement the autocorrelation analysis. This paper presents a set of models and analytical procedures for spatial cross-correlation analysis. By analogy with Moran's index newly expressed in a spatial quadratic form, a theoretical framework is derived for geographical cross-correlation modeling. First, two sets of spatial cross-correlation coefficients are defined, including a global spatial cross-correlation coefficient and local spatial cross-correlation coefficients. Second, a pair of scatterplots of spatial cross-correlation is proposed, and the plots can be used to visually reveal the causality behind spatial systems. Based on the global cross-correlation coefficient, Pearson's correlation coefficient can be decomposed into two parts: direct correlation (partial correlation) and indirect correlation (spatial cross-correlation). As an example, the methodology is applied to the relationships between China's urbanization and economic development to illustrate how to model spatial cross-correlation phenomena. This study is an introduction to developing the theory of spatial cross-correlation, and future geographical spatial analysis might benefit from these models and indexes.

Testing spatial measures of alcohol outlet density with self-rated health in the Australian context: Implications for policy and practice.

PubMed

Badland, Hannah; Mavoa, Suzanne; Livingston, Michael; David, Stephanie; Giles-Corti, Billie

2016-05-01

Reducing access to alcohol is an important and cost-effective strategy for decreasing alcohol consumption and associated harm. Yet this is a less common approach to alcohol control in Australia. The aim of this research was to ascertain which alcohol outlet density spatial measures were related to long-term health outcomes, and the extent to which this differs for those living in more or less disadvantaged neighbourhoods. Existing Australian state-level spatial alcohol policies were reviewed. No appropriate spatial policies were identified; therefore, the literature was used to identify potential alcohol-related spatial measures. Spatial measures of alcohol outlet density were generated in a geographical information system and linked with health survey data drawn from 3141 adults living in metropolitan Melbourne. Logistic regression analysis was used to examine associations between alcohol outlet density measures, self-rated health and area-level disadvantage. Twelve spatial measures of alcohol outlet density were generated. Alcohol outlet density and self-rated health associations varied by area-level disadvantage. For those living in more disadvantaged areas, not having off-licenses available within 800 m, or on-licenses available within 400 m were protective of self-rated health. Local alcohol outlet density may have a more detrimental effect on self-rated health for those living in more disadvantaged neighbourhoods, compared with those living in more advantaged areas. There is a need for spatial alcohol policies to help reduce alcohol-related harm. This research proposes a set of spatial measures to generate a more consistent understanding of alcohol availability in Australia. [Badland H, Mavoa S, Livingston M, David S, Giles-Corti B. Testing spatial measures of alcohol outlet density with self-rated health in the Australian context: Implications for policy and practice. Drug Alcohol Rev 2016;35:298-306]. © 2015 Australasian Professional Society on Alcohol and other Drugs.

A review of second law techniques applicable to basic thermal science research

NASA Astrophysics Data System (ADS)

Drost, M. Kevin; Zamorski, Joseph R.

1988-11-01

This paper reports the results of a review of second law analysis techniques which can contribute to basic research in the thermal sciences. The review demonstrated that second law analysis has a role in basic thermal science research. Unlike traditional techniques, second law analysis accurately identifies the sources and location of thermodynamic losses. This allows the development of innovative solutions to thermal science problems by directing research to the key technical issues. Two classes of second law techniques were identified as being particularly useful. First, system and component investigations can provide information of the source and nature of irreversibilities on a macroscopic scale. This information will help to identify new research topics and will support the evaluation of current research efforts. Second, the differential approach can provide information on the causes and spatial and temporal distribution of local irreversibilities. This information enhances the understanding of fluid mechanics, thermodynamics, and heat and mass transfer, and may suggest innovative methods for reducing irreversibilities.

Sustainable Revitalization in Cultural Heritage Kampong Kauman Surakarta Supported by Spatial Analysis

NASA Astrophysics Data System (ADS)

Musyawaroh, M.; Pitana, T. S.; Masykuri, M.; Nandariyah

2018-02-01

Revitalization is a much-needed for a historic kampong as a settlement, place of business, and as tourist destinations. The research was conducted in Kauman as one of the cultural heritage kampong which was formerly as a residence of abdidalemulamaKeraton who also work as batik entrepreneurs. This study aims to formulate a sustainable revitalization step based on the character of the area and the building. Aspects of sustainable revitalization that analyzed are the physical and non-physical condition of the environment. This research is an applied research with qualitative rationalistic approach supported with spatial distribution analysis through satellite imagery and Arch-GIS. The results revealed that sustainable revitalization for Kaumancan be done through: 1) Physical condition of the environment consists of land and building use, green open space, recreational park and sport activities, streets, drainage network, sewer network, the garbage disposal network; 2) Non-physical of the environment consists of economy, heritage socio-cultural, and the engagement of relevant stakeholders. The difference of this study with others is, this study is a continuation of the Kauman revitalization assistance program which involves community participation to produce a more appropriate solution for the problem of kampong.

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

[Research of Identify Spatial Object Using Spectrum Analysis Technique].

PubMed

Song, Wei; Feng, Shi-qi; Shi, Jing; Xu, Rong; Wang, Gong-chang; Li, Bin-yu; Liu, Yu; Li, Shuang; Cao Rui; Cai, Hong-xing; Zhang, Xi-he; Tan, Yong

2015-06-01

The high precision scattering spectrum of spatial fragment with the minimum brightness of 4.2 and the resolution of 0.5 nm has been observed using spectrum detection technology on the ground. The obvious differences for different types of objects are obtained by the normalizing and discrete rate analysis of the spectral data. Each of normalized multi-frame scattering spectral line shape for rocket debris is identical. However, that is different for lapsed satellites. The discrete rate of the single frame spectrum of normalized space debris for rocket debris ranges from 0.978% to 3.067%, and the difference of oscillation and average value is small. The discrete rate for lapsed satellites ranges from 3.118 4% to 19.472 7%, and the difference of oscillation and average value relatively large. The reason is that the composition of rocket debris is single, while that of the lapsed satellites is complex. Therefore, the spectrum detection technology on the ground can be used to the classification of the spatial fragment.

Precipitation climatology over India: validation with observations and reanalysis datasets and spatial trends

NASA Astrophysics Data System (ADS)

Kishore, P.; Jyothi, S.; Basha, Ghouse; Rao, S. V. B.; Rajeevan, M.; Velicogna, Isabella; Sutterley, Tyler C.

2016-01-01

Changing rainfall patterns have significant effect on water resources, agriculture output in many countries, especially the country like India where the economy depends on rain-fed agriculture. Rainfall over India has large spatial as well as temporal variability. To understand the variability in rainfall, spatial-temporal analyses of rainfall have been studied by using 107 (1901-2007) years of daily gridded India Meteorological Department (IMD) rainfall datasets. Further, the validation of IMD precipitation data is carried out with different observational and different reanalysis datasets during the period from 1989 to 2007. The Global Precipitation Climatology Project data shows similar features as that of IMD with high degree of comparison, whereas Asian Precipitation-Highly-Resolved Observational Data Integration Towards Evaluation data show similar features but with large differences, especially over northwest, west coast and western Himalayas. Spatially, large deviation is observed in the interior peninsula during the monsoon season with National Aeronautics Space Administration-Modern Era Retrospective-analysis for Research and Applications (NASA-MERRA), pre-monsoon with Japanese 25 years Re Analysis (JRA-25), and post-monsoon with climate forecast system reanalysis (CFSR) reanalysis datasets. Among the reanalysis datasets, European Centre for Medium-Range Weather Forecasts Interim Re-Analysis (ERA-Interim) shows good comparison followed by CFSR, NASA-MERRA, and JRA-25. Further, for the first time, with high resolution and long-term IMD data, the spatial distribution of trends is estimated using robust regression analysis technique on the annual and seasonal rainfall data with respect to different regions of India. Significant positive and negative trends are noticed in the whole time series of data during the monsoon season. The northeast and west coast of the Indian region shows significant positive trends and negative trends over western Himalayas and north central Indian region.

Detecting spatial regimes in ecosystems

USGS Publications Warehouse

Sundstrom, Shana M.; Eason, Tarsha; Nelson, R. John; Angeler, David G.; Barichievy, Chris; Garmestani, Ahjond S.; Graham, Nicholas A.J.; Granholm, Dean; Gunderson, Lance; Knutson, Melinda; Nash, Kirsty L.; Spanbauer, Trisha; Stow, Craig A.; Allen, Craig R.

2017-01-01

Research on early warning indicators has generally focused on assessing temporal transitions with limited application of these methods to detecting spatial regimes. Traditional spatial boundary detection procedures that result in ecoregion maps are typically based on ecological potential (i.e. potential vegetation), and often fail to account for ongoing changes due to stressors such as land use change and climate change and their effects on plant and animal communities. We use Fisher information, an information theory-based method, on both terrestrial and aquatic animal data (U.S. Breeding Bird Survey and marine zooplankton) to identify ecological boundaries, and compare our results to traditional early warning indicators, conventional ecoregion maps and multivariate analyses such as nMDS and cluster analysis. We successfully detected spatial regimes and transitions in both terrestrial and aquatic systems using Fisher information. Furthermore, Fisher information provided explicit spatial information about community change that is absent from other multivariate approaches. Our results suggest that defining spatial regimes based on animal communities may better reflect ecological reality than do traditional ecoregion maps, especially in our current era of rapid and unpredictable ecological change.

Evaluation of SOVAT: an OLAP-GIS decision support system for community health assessment data analysis.

PubMed

Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie

2008-06-09

Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture.On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (alpha = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis.

Evaluation of SOVAT: An OLAP-GIS decision support system for community health assessment data analysis

PubMed Central

Scotch, Matthew; Parmanto, Bambang; Monaco, Valerie

2008-01-01

Background Data analysis in community health assessment (CHA) involves the collection, integration, and analysis of large numerical and spatial data sets in order to identify health priorities. Geographic Information Systems (GIS) enable for management and analysis using spatial data, but have limitations in performing analysis of numerical data because of its traditional database architecture. On-Line Analytical Processing (OLAP) is a multidimensional datawarehouse designed to facilitate querying of large numerical data. Coupling the spatial capabilities of GIS with the numerical analysis of OLAP, might enhance CHA data analysis. OLAP-GIS systems have been developed by university researchers and corporations, yet their potential for CHA data analysis is not well understood. To evaluate the potential of an OLAP-GIS decision support system for CHA problem solving, we compared OLAP-GIS to the standard information technology (IT) currently used by many public health professionals. Methods SOVAT, an OLAP-GIS decision support system developed at the University of Pittsburgh, was compared against current IT for data analysis for CHA. For this study, current IT was considered the combined use of SPSS and GIS ("SPSS-GIS"). Graduate students, researchers, and faculty in the health sciences at the University of Pittsburgh were recruited. Each round consisted of: an instructional video of the system being evaluated, two practice tasks, five assessment tasks, and one post-study questionnaire. Objective and subjective measurement included: task completion time, success in answering the tasks, and system satisfaction. Results Thirteen individuals participated. Inferential statistics were analyzed using linear mixed model analysis. SOVAT was statistically significant (α = .01) from SPSS-GIS for satisfaction and time (p < .002). Descriptive results indicated that participants had greater success in answering the tasks when using SOVAT as compared to SPSS-GIS. Conclusion Using SOVAT, tasks were completed more efficiently, with a higher rate of success, and with greater satisfaction, than the combined use of SPSS and GIS. The results from this study indicate a potential for OLAP-GIS decision support systems as a valuable tool for CHA data analysis. PMID:18541037

Spatial and temporal structure of the clinical research based on mesenchymal stromal cells: A network analysis.

PubMed

Monsarrat, Paul; Kemoun, Philippe; Vergnes, Jean-Noel; Sensebe, Luc; Casteilla, Louis; Planat-Benard, Valerie

2017-01-01

Using innovative tools derived from social network analysis, the aims of this study were (i) to decipher the spatial and temporal structure of the research centers network dedicated to the therapeutic uses of mesenchymal stromal cells (MSCs) and (ii) to measure the influence of fields of applications, cellular sources and industry funding on network topography. From each trial using MSCs reported on ClinicalTrials.gov, all research centers were extracted. Networks were generated using Cytoscape 3.2.2, where each center was assimilated to a node, and one trial to an edge connecting two nodes. The analysis included 563 studies. An independent segregation was obvious between continents. Asian, South American and African centers were significantly more isolated than other centers. Isolated centers had fewer advanced phases (P <0.001), completed studies (P = 0.01) and industry-supported studies (P <0.001). Various thematic priorities among continents were identified: the cardiovascular, digestive and nervous system diseases were strongly studied by North America, Europe and Asia, respectively. The choice of cellular sources also affected the network topography; North America was primarily involved in bone-marrow-derived MSC research, whereas Europe and Asia dominated the use of adipose-derived MSCs. Industrial funding was the highest for North American centers (90.5%). Strengthening of international standards and statements with institutional, federal and industrial partners is necessary. More connections would facilitate the transfer of knowledge, sharing of resources, mobility of researchers and advancement of trials. Developing partnerships between industry and academic centers seems beneficial to the advancement of trials across different phases and would facilitate the translation of research discoveries. Copyright © 2017 International Society for Cellular Therapy. Published by Elsevier Inc. All rights reserved.

Diversity, composition, and geographical distribution of microbial communities in California salt marsh sediments

USGS Publications Warehouse

Cordova-Kreylos, A. L.; Cao, Y.; Green, P.G.; Hwang, H.-M.; Kuivila, K.M.; LaMontagne, M.G.; Van De Werfhorst, L. C.; Holden, P.A.; Scow, K.M.

2006-01-01

The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes. Copyright ?? 2006, American Society for Microbiology. All Rights Reserved.

Diversity, Composition, and Geographical Distribution of Microbial Communities in California Salt Marsh Sediments

PubMed Central

Córdova-Kreylos, Ana Lucía; Cao, Yiping; Green, Peter G.; Hwang, Hyun-Min; Kuivila, Kathryn M.; LaMontagne, Michael G.; Van De Werfhorst, Laurie C.; Holden, Patricia A.; Scow, Kate M.

2006-01-01

The Pacific Estuarine Ecosystem Indicators Research Consortium seeks to develop bioindicators of toxicant-induced stress and bioavailability for wetland biota. Within this framework, the effects of environmental and pollutant variables on microbial communities were studied at different spatial scales over a 2-year period. Six salt marshes along the California coastline were characterized using phospholipid fatty acid (PLFA) analysis and terminal restriction fragment length polymorphism (TRFLP) analysis. Additionally, 27 metals, six currently used pesticides, total polychlorinated biphenyls and polycyclic aromatic hydrocarbons, chlordanes, nonachlors, dichlorodiphenyldichloroethane, and dichlorodiphenyldichloroethylene were analyzed. Sampling was performed over large (between salt marshes), medium (stations within a marsh), and small (different channel depths) spatial scales. Regression and ordination analysis suggested that the spatial variation in microbial communities exceeded the variation attributable to pollutants. PLFA analysis and TRFLP canonical correspondence analysis (CCA) explained 74 and 43% of the variation, respectively, and both methods attributed 34% of the variation to tidal cycles, marsh, year, and latitude. After accounting for spatial variation using partial CCA, we found that metals had a greater effect on microbial community composition than organic pollutants had. Organic carbon and nitrogen contents were positively correlated with PLFA biomass, whereas total metal concentrations were positively correlated with biomass and diversity. Higher concentrations of heavy metals were negatively correlated with branched PLFAs and positively correlated with methyl- and cyclo-substituted PLFAs. The strong relationships observed between pollutant concentrations and some of the microbial indicators indicated the potential for using microbial community analyses in assessments of the ecosystem health of salt marshes. PMID:16672478

Fundamental remote science research program. Part 2: Status report of the mathematical pattern recognition and image analysis project

NASA Technical Reports Server (NTRS)

Heydorn, R. P.

1984-01-01

The Mathematical Pattern Recognition and Image Analysis (MPRIA) Project is concerned with basic research problems related to the study of he Earth from remotely sensed measurements of its surface characteristics. The program goal is to better understand how to analyze the digital image that represents the spatial, spectral, and temporal arrangement of these measurements for purposing of making selected inferences about the Earth. This report summarizes the progress that has been made toward this program goal by each of the principal investigators in the MPRIA Program.

Developing spatial inequalities in carbon appropriation: a sociological analysis of changing local emissions across the United States.

PubMed

Elliott, James R; Clement, Matthew Thomas

2015-05-01

This study examines an overlooked dynamic in sociological research on greenhouse gas emissions: how local areas appropriate the global carbon cycle for use and exchange purposes as they develop. Drawing on theories of place and space, we hypothesize that development differentially drives and spatially decouples use- and exchange-oriented emissions at the local level. To test our hypotheses, we integrate longitudinal, county-level data on residential and industrial emissions from the Vulcan Project with demographic, economic and environmental data from the U.S. Census Bureau and National Land Change Database. Results from spatial regression models with two-way fixed-effects indicate that alongside innovations and efficiencies capable of reducing environmentally harmful effects of development comes a spatial disarticulation between carbon-intensive production and consumption within as well as across societies. Implications for existing theory, methods and policy are discussed. Copyright © 2015 Elsevier Inc. All rights reserved.

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.

Multi-scale analysis of a household level agent-based model of landcover change.

PubMed

Evans, Tom P; Kelley, Hugh

2004-08-01

Scale issues have significant implications for the analysis of social and biophysical processes in complex systems. These same scale implications are likewise considerations for the design and application of models of landcover change. Scale issues have wide-ranging effects from the representativeness of data used to validate models to aggregation errors introduced in the model structure. This paper presents an analysis of how scale issues affect an agent-based model (ABM) of landcover change developed for a research area in the Midwest, USA. The research presented here explores how scale factors affect the design and application of agent-based landcover change models. The ABM is composed of a series of heterogeneous agents who make landuse decisions on a portfolio of cells in a raster-based programming environment. The model is calibrated using measures of fit derived from both spatial composition and spatial pattern metrics from multi-temporal landcover data interpreted from historical aerial photography. A model calibration process is used to find a best-fit set of parameter weights assigned to agents' preferences for different landuses (agriculture, pasture, timber production, and non-harvested forest). Previous research using this model has shown how a heterogeneous set of agents with differing preferences for a portfolio of landuses produces the best fit to landcover changes observed in the study area. The scale dependence of the model is explored by varying the resolution of the input data used to calibrate the model (observed landcover), ancillary datasets that affect land suitability (topography), and the resolution of the model landscape on which agents make decisions. To explore the impact of these scale relationships the model is run with input datasets constructed at the following spatial resolutions: 60, 90, 120, 150, 240, 300 and 480 m. The results show that the distribution of landuse-preference weights differs as a function of scale. In addition, with the gradient descent model fitting method used in this analysis the model was not able to converge to an acceptable fit at the 300 and 480 m spatial resolutions. This is a product of the ratio of the input cell resolution to the average parcel size in the landscape. This paper uses these findings to identify scale considerations in the design, development, validation and application of ABMs of landcover change.

Drugs at the campsite: Socio-spatial relations and drug use at music festivals.

PubMed

Dilkes-Frayne, Ella

2016-07-01

Music festivals have received relatively little research attention despite being key sites for alcohol and drug use among young people internationally. Research into music festivals and the social contexts of drug use more generally, has tended to focus on social and cultural processes without sufficient regard for the mediating role of space and spatial processes. Adopting a relational approach to space and the social, from Actor-Network Theory and human geography, I examine how socio-spatial relations are generated in campsites at multiple-day music festivals. The data are drawn from ethnographic observations at music festivals around Melbourne, Australia; interviews with 18-23 year olds; and participant-written diaries. Through the analysis, the campsite is revealed as a space in process, the making of which is bound up in how drug use unfolds. Campsite relations mediate the formation of drug knowledge and norms, informal harm reduction practices, access to and exchange of drugs, and rest and recovery following drug use. Greater attendance to socio-spatial relations affords new insights regarding how festival spaces and their social effects are generated, and how they give rise to particular drug use practices. These findings also point to how festival harm reduction strategies might be enhanced through the promotion of enabling socio-spatial relations. Copyright © 2015 Elsevier B.V. All rights reserved.

The case against specialized visual-spatial short-term memory.

PubMed

Morey, Candice C

2018-05-24

The dominant paradigm for understanding working memory, or the combination of the perceptual, attentional, and mnemonic processes needed for thinking, subdivides short-term memory (STM) according to whether memoranda are encoded in aural-verbal or visual formats. This traditional dissociation has been supported by examples of neuropsychological patients who seem to selectively lack STM for either aural-verbal, visual, or spatial memoranda, and by experimental research using dual-task methods. Though this evidence is the foundation of assumptions of modular STM systems, the case it makes for a specialized visual STM system is surprisingly weak. I identify the key evidence supporting a distinct verbal STM system-patients with apparent selective damage to verbal STM and the resilience of verbal short-term memories to general dual-task interference-and apply these benchmarks to neuropsychological and experimental investigations of visual-spatial STM. Contrary to the evidence on verbal STM, patients with apparent visual or spatial STM deficits tend to experience a wide range of additional deficits, making it difficult to conclude that a distinct short-term store was damaged. Consistently with this, a meta-analysis of dual-task visual-spatial STM research shows that robust dual-task costs are consistently observed regardless of the domain or sensory code of the secondary task. Together, this evidence suggests that positing a specialized visual STM system is not necessary. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Implementation of AN Agricultural Environmental Information System (aeis) for the Sanjiang Plain, Ne-China

NASA Astrophysics Data System (ADS)

Zhao, Q.; Brocks, S.; Lenz-Wiedemann, V.; Miao, Y.; Jiang, R.; Chen, X.; Zhang, F.; Bareth, G.

2012-07-01

The Sino-German Project between the China Agricultural University and the University of Cologne, Germany, focuses on regional agro-ecosystem modelling. One major focus of the cooperation activity is the establishment of joint rice field experiment research in Jiansanjiang, located in the Sanjiang Plain (Heilongjiang Province, north-eastern part of China), to investigate the different agricultural practices and their impact on yield and environment. An additional task is to set-up an Agricultural Environmental Information System (AEIS) for the Sanjiang Plain (SJP), which covers more than 100 000 km2. Research groups from Geography (e.g. GIS & Remote Sensing) and Plant Nutrition (e.g. Precision Agriculture) are involved in the project. The major aim of the AEIS for the SJP is to provide information about (i) agriculture in the region, (ii) the impact of agricultural practices on the environment, and (iii) simulation scenarios for sustainable strategies. Consequently, the AEIS for the SJP provides information for decision support and therefore could be regarded as a Spatial Decision Support System (SDSS), too. The investigation of agricultural and environmental issues has a spatial context, which requires the management, handling, and analysis of spatial data. The use of GIS enables the capture, storage, analysis and presentation of spatial data. Therefore, GIS is the major tool for the set-up of the AEIS for the SJP. This contribution presents the results of linking agricultural statistics with GIS to provide information about agriculture in the SJP and discusses the benefits of this method as well as the integration of methods to produce new data.

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

NASA Astrophysics Data System (ADS)

Mayer, J. M.; Stead, D.

2017-04-01

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

Land use/land cover and land capability data for evaluating land utilization and official land use planning in Indramayu Regency, West Java, Indonesia

NASA Astrophysics Data System (ADS)

Ambarwulan, W.; Widiatmaka; Nahib, I.

2018-05-01

Land utilization in Indonesia is regulated in an official spatial land use planning (OSLUP), stipulated by government regulations. However in fact, land utilizations are often develops inconsistent with regulations. OSLUP itself is also not usually compatible with sustainable land utilizations. This study aims to evaluate current land utilizations and OSLUP in Indramayu Regency, West Java. The methodology used is the integrated analysis using land use and land cover (LU/LC) data, land capability data and spatial pattern in OSLUP. Actual LU/LC are interpreted using SPOT-6 imagery of 2014. The spatial data of land capabilities are derived from land capability classification using field data and laboratory analysis. The confrontation between these spatial data is interpreted in terms of future direction for sustainable land use planning. The results shows that Indramayu regency consists of 8 types of LU/LC. Land capability in research area range from class II to VIII. Only a small portion of the land in Indramayu has been used in accordance with land capability, but most of the land is used exceeding its land capability.

Spatio-temporal models of mental processes from fMRI.

PubMed

Janoos, Firdaus; Machiraju, Raghu; Singh, Shantanu; Morocz, Istvan Ákos

2011-07-15

Understanding the highly complex, spatially distributed and temporally organized phenomena entailed by mental processes using functional MRI is an important research problem in cognitive and clinical neuroscience. Conventional analysis methods focus on the spatial dimension of the data discarding the information about brain function contained in the temporal dimension. This paper presents a fully spatio-temporal multivariate analysis method using a state-space model (SSM) for brain function that yields not only spatial maps of activity but also its temporal structure along with spatially varying estimates of the hemodynamic response. Efficient algorithms for estimating the parameters along with quantitative validations are given. A novel low-dimensional feature-space for representing the data, based on a formal definition of functional similarity, is derived. Quantitative validation of the model and the estimation algorithms is provided with a simulation study. Using a real fMRI study for mental arithmetic, the ability of this neurophysiologically inspired model to represent the spatio-temporal information corresponding to mental processes is demonstrated. Moreover, by comparing the models across multiple subjects, natural patterns in mental processes organized according to different mental abilities are revealed. Copyright © 2011 Elsevier Inc. All rights reserved.

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.

Accounting for regional background and population size in the detection of spatial clusters and outliers using geostatistical filtering and spatial neutral models: the case of lung cancer in Long Island, New York

PubMed Central

Goovaerts, Pierre; Jacquez, Geoffrey M

2004-01-01

Background Complete Spatial Randomness (CSR) is the null hypothesis employed by many statistical tests for spatial pattern, such as local cluster or boundary analysis. CSR is however not a relevant null hypothesis for highly complex and organized systems such as those encountered in the environmental and health sciences in which underlying spatial pattern is present. This paper presents a geostatistical approach to filter the noise caused by spatially varying population size and to generate spatially correlated neutral models that account for regional background obtained by geostatistical smoothing of observed mortality rates. These neutral models were used in conjunction with the local Moran statistics to identify spatial clusters and outliers in the geographical distribution of male and female lung cancer in Nassau, Queens, and Suffolk counties, New York, USA. Results We developed a typology of neutral models that progressively relaxes the assumptions of null hypotheses, allowing for the presence of spatial autocorrelation, non-uniform risk, and incorporation of spatially heterogeneous population sizes. Incorporation of spatial autocorrelation led to fewer significant ZIP codes than found in previous studies, confirming earlier claims that CSR can lead to over-identification of the number of significant spatial clusters or outliers. Accounting for population size through geostatistical filtering increased the size of clusters while removing most of the spatial outliers. Integration of regional background into the neutral models yielded substantially different spatial clusters and outliers, leading to the identification of ZIP codes where SMR values significantly depart from their regional background. Conclusion The approach presented in this paper enables researchers to assess geographic relationships using appropriate null hypotheses that account for the background variation extant in real-world systems. In particular, this new methodology allows one to identify geographic pattern above and beyond background variation. The implementation of this approach in spatial statistical software will facilitate the detection of spatial disparities in mortality rates, establishing the rationale for targeted cancer control interventions, including consideration of health services needs, and resource allocation for screening and diagnostic testing. It will allow researchers to systematically evaluate how sensitive their results are to assumptions implicit under alternative null hypotheses. PMID:15272930

Multi-criteria decision analysis in conservation planning: Designing conservation area networks in San Diego County

NASA Astrophysics Data System (ADS)

MacDonald, Garrick Richard

To limit biodiversity loss caused by human activity, conservation planning must protect biodiversity while considering socio-economic cost criteria. This research aimed to determine the effects of socio-economic criteria and spatial configurations on the development of CANs for three species with different distribution patterns, while simultaneously attempting to address the uncertainty and sensitivity of CANs produced by ConsNet. The socio-economic factors and spatial criteria included the cost of land, population density, agricultural output value, area, average cluster area, number of clusters, shape, and perimeter. Three sensitive mammal species with different distribution patterns were selected and included the Bobcat, Ringtail, and a custom created mammal distribution. Forty problems and the corresponding number of CANs were formulated and computed by running each predicted presence species model with and without the four different socioeconomic threshold groups at two different resolutions. Thirty-two percent less area was conserved after considering multiple socio-economic constraints and spatial configurations in comparison to CANs that did not consider multiple socio-economic constraints and spatial configurations. Without including socio-economic costs, ConsNet's ALL_CELLS heuristic solution was the highest ranking CAN. After considering multiple socio-economic costs, the number one ranking CAN was no longer the ALL_CELLS heuristic solution, but a spatially different meta-heuristic solution. The effects of multiple constraints and objectives on the design of CANs with different distribution patterns did not vary significantly across the criteria. The CANs produced by ConsNet appeared to demonstrate some uncertainty surrounding particular criteria, but did not demonstrate substantial uncertainty across all criteria used to rank the CANs. Similarly, the range of socio-economic criteria thresholds did not have a substantial impact. ConsNet was very applicable to the research project, however, it did exhibit a few limitations. Both the advantages and disadvantages of ConsNet should be considered before using ConsNet for future conservation planning projects. The research project is an example of a large data scenario undertaken with a multiple criteria decision analysis (MCDA) approach.

Advanced analysis of forest fire clustering

NASA Astrophysics Data System (ADS)

Kanevski, Mikhail; Pereira, Mario; Golay, Jean

2017-04-01

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

Covariate selection with iterative principal component analysis for predicting physical

USDA-ARS?s Scientific Manuscript database

Local and regional soil data can be improved by coupling new digital soil mapping techniques with high resolution remote sensing products to quantify both spatial and absolute variation of soil properties. The objective of this research was to advance data-driven digital soil mapping techniques for ...

ANALYSIS OF ONE-DIMENSIONAL SOLUTE TRANSPORT THROUGH POROUS MEDIA WITH SPATIALLY VARIABLE RETARDATION FACTOR. (R825689C037)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

An analysis of historic and projected climate scenarios in the Western United States using hydrologic landscape classification.

EPA Science Inventory

: Identifying areas of similar hydrology within the United States and its regions (hydrologic landscapes - HLs) is an active area of research. HLs are being used to construct spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, a...

An analysis of historic and projected climate scenarios in the Western united States using hydrologic landscape classification

EPA Science Inventory

Identifying areas of similar hydrology within the United States and its regions (Hydrologic landscapes - HLs) is an active area of research. HLs have been used to make spatially distributed assessments of variability in streamflow and climatic response in Oregon, Alaska, and the ...

Sensitivity to Landscape Features: A Spatial Analysis of Field Geoscientists on the Move

ERIC Educational Resources Information Center

Baker, Kathleen M.; Petcovic, L. Heather

2016-01-01

Intelligent behavior in everyday contexts may depend on both ability and an individual's disposition toward using that ability. Research into patterns of thinking has identified three logically distinct components necessary for dispositional behavior: ability, inclination, and sensitivity. Surprisingly, sensitivity appears to be the most common…

FLUVIAL RESPONSE A DECADE AFTER WILDFIRE IN THE NORTHERN YELLOWSTONE ECOSYSTEM: A SPATIALLY EXPLICIT ANALYSIS. (R827638)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Locating Chicago's Charter Schools: A Socio-Spatial Analysis

ERIC Educational Resources Information Center

LaFleur, Jennifer C.

2016-01-01

This project contributes to the body of research examining the implications of the geographic location of charter schools for student access, especially in high-poverty communities. Using geographic information systems (GIS) software, this paper uses data from the U.S. Census American Community Survey to identify the socioeconomic characteristics…

Quantifying uncertainty in forest nutrient budgets

Treesearch

Ruth D. Yanai; Carrie R. Levine; Mark B. Green; John L. Campbell

2012-01-01

Nutrient budgets for forested ecosystems have rarely included error analysis, in spite of the importance of uncertainty to interpretation and extrapolation of the results. Uncertainty derives from natural spatial and temporal variation and also from knowledge uncertainty in measurement and models. For example, when estimating forest biomass, researchers commonly report...

Update and review of accuracy assessment techniques for remotely sensed data

NASA Technical Reports Server (NTRS)

Congalton, R. G.; Heinen, J. T.; Oderwald, R. G.

1983-01-01

Research performed in the accuracy assessment of remotely sensed data is updated and reviewed. The use of discrete multivariate analysis techniques for the assessment of error matrices, the use of computer simulation for assessing various sampling strategies, and an investigation of spatial autocorrelation techniques are examined.

REGIONAL VULNERABILITY ASSESSMENT (REVA) IMPROVING ENVIRONMENTAL DECISION MAKING THROUGH CLIENT PARTNERSHIPS

EPA Science Inventory

The Regional Vulnerability Assessment (ReV A) Program is an applied research program t,1at is focusing on using spatial information and model results to support environmental decision-making at regional- down to local-scales. Re VA has developed analysis and assessment methods to...

A Deep Similarity Metric Learning Model for Matching Text Chunks to Spatial Entities

NASA Astrophysics Data System (ADS)

Ma, K.; Wu, L.; Tao, L.; Li, W.; Xie, Z.

2017-12-01

The matching of spatial entities with related text is a long-standing research topic that has received considerable attention over the years. This task aims at enrich the contents of spatial entity, and attach the spatial location information to the text chunk. In the data fusion field, matching spatial entities with the corresponding describing text chunks has a big range of significance. However, the most traditional matching methods often rely fully on manually designed, task-specific linguistic features. This work proposes a Deep Similarity Metric Learning Model (DSMLM) based on Siamese Neural Network to learn similarity metric directly from the textural attributes of spatial entity and text chunk. The low-dimensional feature representation of the space entity and the text chunk can be learned separately. By employing the Cosine distance to measure the matching degree between the vectors, the model can make the matching pair vectors as close as possible. Mearnwhile, it makes the mismatching as far apart as possible through supervised learning. In addition, extensive experiments and analysis on geological survey data sets show that our DSMLM model can effectively capture the matching characteristics between the text chunk and the spatial entity, and achieve state-of-the-art performance.

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.

Understanding Gaps in Research Networks: Using "Spatial Reasoning" as a Window into the Importance of Networked Educational Research

ERIC Educational Resources Information Center

Bruce, Catherine D.; Davis, Brent; Sinclair, Nathalie; McGarvey, Lynn; Hallowell, David; Drefs, Michelle; Francis, Krista; Hawes, Zachary; Moss, Joan; Mulligan, Joanne; Okamoto, Yukari; Whiteley, Walter; Woolcott, Geoff

2017-01-01

This paper finds its origins in a multidisciplinary research group's efforts to assemble a review of research in order to better appreciate how "spatial reasoning" is understood and investigated across academic disciplines. We first collaborated to create a historical map of the development of spatial reasoning across key disciplines…

Understanding Organics in Meteorites and the Pre-Biotic Environment

NASA Technical Reports Server (NTRS)

Zare, Richard N.

2003-01-01

(1) Refinement of the analytic capabilities of our experiment via characterization of molecule-specific response and the effects upon analysis of the type of sample under investigation; (2) Measurement of polycyclic aromatic hydrocarbons (PAHs) with high sensitivity and spatial resolution within extraterrestrial samples; (3) Investigation of the interstellar reactions of PAHs via the analysis of species formed in systems modeling dust grains and ices; (4) Investigations into the potential role of PAHs in prebiotic and early biotic chemistry via photoreactions of PAHs under simulated prebiotic Earth conditions. To meet these objectives, we use microprobe laser-desorption, laser-ionization mass spectrometry (MuL(exp 2)MS), which is a sensitive, selective, and spatially resolved technique for detection of aromatic compounds. Appendix A presents a description of the MuL(exp 2)MS technique. The initial grant proposal was for a three-year funding period, while the award was given for a one-year interim period. Because of this change in time period, emphasis was shifted from the first research goal, which was more development-oriented, in order to focus more on the other analysis-oriented goals. The progress made on each of the four research areas is given below.

Geomatics for Maritime Parks and Preserved Areas

NASA Astrophysics Data System (ADS)

Lo Tauro, Agata

2009-11-01

The aim of this research is to use hyperspectral MIVIS data for protection of sensitive cultural, natural resources, Nature Reserves and maritime parks. A knowledge of the distribution of submerged vegetation is useful to monitor the health of ecosystems in coastal areas. The objective of this project was to develop a new methodology within geomatic environment to facilitate the analysis and application of Local Institutions who are not familiar with Spatial Analysis softwares in order to implement new research activities in this field of study. Field controls may be carried out with the support of accurate and novel in situ analysis in order to determine the training sites for the novel tested classification. The methodology applied demonstrates that the combination of hyperspectral sensors and ESA Remote Sensing (RS) data can be used to analyse thematic cartography of submerged vegetation and land use analysis for Sustainable Development. This project will be implemented for Innovative Educational and Research Programmes.

Implications of construction method and spatial scale on measures of the built environment.

PubMed

Strominger, Julie; Anthopolos, Rebecca; Miranda, Marie Lynn

2016-04-28

Research surrounding the built environment (BE) and health has resulted in inconsistent findings. Experts have identified the need to examine methodological choices, such as development and testing of BE indices at varying spatial scales. We sought to examine the impact of construction method and spatial scale on seven measures of the BE using data collected at two time points. The Children's Environmental Health Initiative conducted parcel-level assessments of 57 BE variables in Durham, NC (parcel N = 30,319). Based on a priori defined variable groupings, we constructed seven mutually exclusive BE domains (housing damage, property disorder, territoriality, vacancy, public nuisances, crime, and tenancy). Domain-based indices were developed according to four different index construction methods that differentially account for number of parcels and parcel area. Indices were constructed at the census block level and two alternative spatial scales that better depict the larger neighborhood context experienced by local residents: the primary adjacency community and secondary adjacency community. Spearman's rank correlation was used to assess if indices and relationships among indices were preserved across methods. Territoriality, public nuisances, and tenancy were weakly to moderately preserved across methods at the block level while all other indices were well preserved. Except for the relationships between public nuisances and crime or tenancy, and crime and housing damage or territoriality, relationships among indices were poorly preserved across methods. The number of indices affected by construction method increased as spatial scale increased, while the impact of construction method on relationships among indices varied according to spatial scale. We found that the impact of construction method on BE measures was index and spatial scale specific. Operationalizing and developing BE measures using alternative methods at varying spatial scales before connecting to health outcomes allows researchers to better understand how methodological decisions may affect associations between health outcomes and BE measures. To ensure that associations between the BE and health outcomes are not artifacts of methodological decisions, researchers would be well-advised to conduct sensitivity analysis using different construction methods. This approach may lead to more robust results regarding the BE and health outcomes.

Study of urban spatial utilization on socio-cultural and environment based on sustainability index (study in Denpasar city)

NASA Astrophysics Data System (ADS)

Wiryananda, N. G. A. K.; Hasibuan, H. S.; Madiasworo, T.

2018-03-01

The rapid development of tourism and population growth in Denpasar City stimulated the dynamic changes in the spatial utilization. This study aims to analyse the impact of spatial utilization on sociocultural and environment and formulate the sustainable spatial utilization that accommodate both social and environmental aspects. This research uses methods of spatial analysis and sustainability index. The results showed that during the period of 2011 to 2015 there was an increase of settlement and tourism land uses, meanwhile at the same period the paddy field decreased. The impact of spatial utilization on sociocultural leads to unsustainable, that showed by the decreasing of the sociocultural index from 1.038 in 2011 to 1.036 in 2015. The low of sociocultural index was stated by the increasing poverty, the obedience of traditional rules of purity radius of Temple and the height limit of the building. The impact of spatial utilization on environmental leads to unsustainable, with the environmental index of 1.065 in 2011 decreased to 1.056 in 2015. The decline of environmental index is due to reduced green open space and paddy field. The strategy formulation of sustainable spatial utilization is done by integrating traditional rules into spatial planning, plan the vertical building, strengthening implementation of traditional rules, implementation of perennial paddy field, and the establishment of traditional task control unit of spatial control.

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.

Electrophysiological Evidence for Domain-General Processes in Task-Switching

PubMed Central

Capizzi, Mariagrazia; Ambrosini, Ettore; Arbula, Sandra; Mazzonetto, Ilaria; Vallesi, Antonino

2016-01-01

The ability to flexibly switch between tasks is a hallmark of cognitive control. Despite previous studies that have investigated whether different task-switching types would be mediated by distinct or overlapping neural mechanisms, no definitive consensus has been reached on this question yet. Here, we aimed at directly addressing this issue by recording the event-related potentials (ERPs) elicited by two types of task-switching occurring in the context of spatial and verbal cognitive domains. Source analysis was also applied to the ERP data in order to track the spatial dynamics of brain activity underlying task-switching abilities. In separate blocks of trials, participants had to perform either spatial or verbal switching tasks both of which employed the same type of stimuli. The ERP analysis, which was carried out through a channel- and time-uninformed mass univariate approach, showed no significant differences between the spatial and verbal domains in the modulation of switch and repeat trials. Specifically, relative to repeat trials, switch trials in both domains were associated with a first larger positivity developing over left parieto-occipital electrodes and with a subsequent larger negativity distributed over mid-left fronto-central sites. The source analysis reconstruction for the two ERP components complemented these findings by highlighting the involvement of left-lateralized prefrontal areas in task-switching. Overall, our results join and extend recent research confirming the existence of left-lateralized domain-general task-switching processes. PMID:27047366

Using Spatial Multiple Regression to Identify Intrinsic Connectivity Networks Involved in Working Memory Performance

PubMed Central

Gordon, Evan M.; Stollstorff, Melanie; Vaidya, Chandan J.

2012-01-01

Many researchers have noted that the functional architecture of the human brain is relatively invariant during task performance and the resting state. Indeed, intrinsic connectivity networks (ICNs) revealed by resting-state functional connectivity analyses are spatially similar to regions activated during cognitive tasks. This suggests that patterns of task-related activation in individual subjects may result from the engagement of one or more of these ICNs; however, this has not been tested. We used a novel analysis, spatial multiple regression, to test whether the patterns of activation during an N-back working memory task could be well described by a linear combination of ICNs delineated using Independent Components Analysis at rest. We found that across subjects, the cingulo-opercular Set Maintenance ICN, as well as right and left Frontoparietal Control ICNs, were reliably activated during working memory, while Default Mode and Visual ICNs were reliably deactivated. Further, involvement of Set Maintenance, Frontoparietal Control, and Dorsal Attention ICNs was sensitive to varying working memory load. Finally, the degree of left Frontoparietal Control network activation predicted response speed, while activation in both left Frontoparietal Control and Dorsal Attention networks predicted task accuracy. These results suggest that a close relationship between resting-state networks and task-evoked activation is functionally relevant for behavior, and that spatial multiple regression analysis is a suitable method for revealing that relationship. PMID:21761505

Online data analysis using Web GDL

NASA Astrophysics Data System (ADS)

Jaffey, A.; Cheung, M.; Kobashi, A.

2008-12-01

The ever improving capability of modern astronomical instruments to capture data at high spatial resolution and cadence is opening up unprecedented opportunities for scientific discovery. When data sets become so large that they cannot be easily transferred over the internet, the researcher must find alternative ways to perform data analysis. One strategy is to bring the data analysis code to where the data resides. We present Web GDL, an implementation of GDL (GNU Data Language, open source incremental compiler compatible with IDL) that allows users to perform interactive data analysis within a web browser.

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

PubMed

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

2017-08-07

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

Estimating Biofuel Feedstock Water Footprints Using System Dynamics

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

Inman, Daniel; Warner, Ethan; Stright, Dana

Increased biofuel production has prompted concerns about the environmental tradeoffs of biofuels compared to petroleum-based fuels. Biofuel production in general, and feedstock production in particular, is under increased scrutiny. Water footprinting (measuring direct and indirect water use) has been proposed as one measure to evaluate water use in the context of concerns about depleting rural water supplies through activities such as irrigation for large-scale agriculture. Water footprinting literature has often been limited in one or more key aspects: complete assessment across multiple water stocks (e.g., vadose zone, surface, and ground water stocks), geographical resolution of data, consistent representation of manymore » feedstocks, and flexibility to perform scenario analysis. We developed a model called BioSpatial H2O using a system dynamics modeling and database framework. BioSpatial H2O could be used to consistently evaluate the complete water footprints of multiple biomass feedstocks at high geospatial resolutions. BioSpatial H2O has the flexibility to perform simultaneous scenario analysis of current and potential future crops under alternative yield and climate conditions. In this proof-of-concept paper, we modeled corn grain (Zea mays L.) and soybeans (Glycine max) under current conditions as illustrative results. BioSpatial H2O links to a unique database that houses annual spatially explicit climate, soil, and plant physiological data. Parameters from the database are used as inputs to our system dynamics model for estimating annual crop water requirements using daily time steps. Based on our review of the literature, estimated green water footprints are comparable to other modeled results, suggesting that BioSpatial H2O is computationally sound for future scenario analysis. Our modeling framework builds on previous water use analyses to provide a platform for scenario-based assessment. BioSpatial H2O's system dynamics is a flexible and user-friendly interface for on-demand, spatially explicit, water use scenario analysis for many US agricultural crops. Built-in controls permit users to quickly make modifications to the model assumptions, such as those affecting yield, and to see the implications of those results in real time. BioSpatial H2O's dynamic capabilities and adjustable climate data allow for analyses of water use and management scenarios to inform current and potential future bioenergy policies. The model could also be adapted for scenario analysis of alternative climatic conditions and comparison of multiple crops. The results of such an analysis would help identify risks associated with water use competition among feedstocks in certain regions. Results could also inform research and development efforts that seek to reduce water-related risks of biofuel pathways.« less

Spatial and temporal changes in household structure locations using high-resolution satellite imagery for population assessment: an analysis in southern Zambia, 2006-2011.

PubMed

Shields, Timothy; Pinchoff, Jessie; Lubinda, Jailos; Hamapumbu, Harry; Searle, Kelly; Kobayashi, Tamaki; Thuma, Philip E; Moss, William J; Curriero, Frank C

2016-05-31

Satellite imagery is increasingly available at high spatial resolution and can be used for various purposes in public health research and programme implementation. Comparing a census generated from two satellite images of the same region in rural southern Zambia obtained four and a half years apart identified patterns of household locations and change over time. The length of time that a satellite image-based census is accurate determines its utility. Households were enumerated manually from satellite images obtained in 2006 and 2011 of the same area. Spatial statistics were used to describe clustering, cluster detection, and spatial variation in the location of households. A total of 3821 household locations were enumerated in 2006 and 4256 in 2011, a net change of 435 houses (11.4% increase). Comparison of the images indicated that 971 (25.4%) structures were added and 536 (14.0%) removed. Further analysis suggested similar household clustering in the two images and no substantial difference in concentration of households across the study area. Cluster detection analysis identified a small area where significantly more household structures were removed than expected; however, the amount of change was of limited practical significance. These findings suggest that random sampling of households for study participation would not induce geographic bias if based on a 4.5-year-old image in this region. Application of spatial statistical methods provides insights into the population distribution changes between two time periods and can be helpful in assessing the accuracy of satellite imagery.

Modelling space of spread Dengue Hemorrhagic Fever (DHF) in Central Java use spatial durbin model

NASA Astrophysics Data System (ADS)

Ispriyanti, Dwi; Prahutama, Alan; Taryono, Arkadina PN

2018-05-01

Dengue Hemorrhagic Fever is one of the major public health problems in Indonesia. From year to year, DHF causes Extraordinary Event in most parts of Indonesia, especially Central Java. Central Java consists of 35 districts or cities where each region is close to each other. Spatial regression is an analysis that suspects the influence of independent variables on the dependent variables with the influences of the region inside. In spatial regression modeling, there are spatial autoregressive model (SAR), spatial error model (SEM) and spatial autoregressive moving average (SARMA). Spatial Durbin model is the development of SAR where the dependent and independent variable have spatial influence. In this research dependent variable used is number of DHF sufferers. The independent variables observed are population density, number of hospitals, residents and health centers, and mean years of schooling. From the multiple regression model test, the variables that significantly affect the spread of DHF disease are the population and mean years of schooling. By using queen contiguity and rook contiguity, the best model produced is the SDM model with queen contiguity because it has the smallest AIC value of 494,12. Factors that generally affect the spread of DHF in Central Java Province are the number of population and the average length of school.

[Analysis of influence on spatial distribution of fishing ground for Antarctic krill fishery in the northern South Shetland Islands based on GWR model].

PubMed

Chen, Lyu Feng; Zhu, Guo Ping

2018-03-01

Based on Antarctic krill fishery and marine environmental data collected by scientific observers, using geographically weighted regression (GWR) model, we analyzed the effects of the factors with spatial attributes, i.e., depth of krill swarm (DKS) and distance from fishing position to shore (DTS), and sea surface temperature (SST), on the spatial distribution of fishing ground in the northern South Shetland Islands. The results showed that there was no significant aggregation in spatial distribution of catch per unit fishing effort (CPUE). Spatial autocorrelations (positive) among three factors were observed in 2010 and 2013, but were not in 2012 and 2016. Results from GWR model showed that the extent for the impacts on spatial distribution of CPUEs varied among those three factors, following the order DKS>SST>DTS. Compared to the DKS and DTS, the impact of SST on the spatial distribution of CPUEs presented adverse trend in the eastern and western parts of the South Shetland Islands. Negative correlations occurred for the spatial effects of DKS and DTS on distribution of CPUEs, though with inter-annual and regional variation. Our results provide metho-dological reference for researches on the underlying mechanism for fishing ground formation for Antarctic krill fishery.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

NASA Astrophysics Data System (ADS)

Giraldo, Mario A.; Bosch, David; Madden, Marguerite; Usery, Lynn; Kvien, Craig

2008-08-01

SummaryThis research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network.

Landscape complexity and soil moisture variation in south Georgia, USA, for remote sensing applications

USGS Publications Warehouse

Giraldo, M.A.; Bosch, D.; Madden, M.; Usery, L.; Kvien, Craig

2008-01-01

This research addressed the temporal and spatial variation of soil moisture (SM) in a heterogeneous landscape. The research objective was to investigate soil moisture variation in eight homogeneous 30 by 30 m plots, similar to the pixel size of a Landsat Thematic Mapper (TM) or Enhanced Thematic Mapper plus (ETM+) image. The plots were adjacent to eight stations of an in situ soil moisture network operated by the United States Department of Agriculture-Agriculture Research Service USDA-ARS in Tifton, GA. We also studied five adjacent agricultural fields to examine the effect of different landuses/land covers (LULC) (grass, orchard, peanuts, cotton and bare soil) on the temporal and spatial variation of soil moisture. Soil moisture field data were collected on eight occasions throughout 2005 and January 2006 to establish comparisons within and among eight homogeneous plots. Consistently throughout time, analysis of variance (ANOVA) showed high variation in the soil moisture behavior among the plots and high homogeneity in the soil moisture behavior within them. A precipitation analysis for the eight sampling dates throughout the year 2005 showed similar rainfall conditions for the eight study plots. Therefore, soil moisture variation among locations was explained by in situ local conditions. Temporal stability geostatistical analysis showed that soil moisture has high temporal stability within the small plots and that a single point reading can be used to monitor soil moisture status for the plot within a maximum 3% volume/volume (v/v) soil moisture variation. Similarly, t-statistic analysis showed that soil moisture status in the upper soil layer changes within 24 h. We found statistical differences in the soil moisture between the different LULC in the agricultural fields as well as statistical differences between these fields and the adjacent 30 by 30 m plots. From this analysis, it was demonstrated that spatial proximity is not enough to produce similar soil moisture, since t-test's among adjacent plots with different LULCs showed significant differences. These results confirm that a remote sensing approach that considers homogeneous LULC landscape fragments can be used to identify landscape units of similar soil moisture behavior under heterogeneous landscapes. In addition, the in situ USDA-ARS network will serve better in remote sensing studies in which sensors with fine spatial resolution are evaluated. This study is a first step towards identifying landscape units that can be monitored using the single point reading of the USDA-ARS stations network. ?? 2008 Elsevier B.V.

Use of artificial neural network for spatial rainfall analysis

NASA Astrophysics Data System (ADS)

Paraskevas, Tsangaratos; Dimitrios, Rozos; Andreas, Benardos

2014-04-01

In the present study, the precipitation data measured at 23 rain gauge stations over the Achaia County, Greece, were used to estimate the spatial distribution of the mean annual precipitation values over a specific catchment area. The objective of this work was achieved by programming an Artificial Neural Network (ANN) that uses the feed-forward back-propagation algorithm as an alternative interpolating technique. A Geographic Information System (GIS) was utilized to process the data derived by the ANN and to create a continuous surface that represented the spatial mean annual precipitation distribution. The ANN introduced an optimization procedure that was implemented during training, adjusting the hidden number of neurons and the convergence of the ANN in order to select the best network architecture. The performance of the ANN was evaluated using three standard statistical evaluation criteria applied to the study area and showed good performance. The outcomes were also compared with the results obtained from a previous study in the area of research which used a linear regression analysis for the estimation of the mean annual precipitation values giving more accurate results. The information and knowledge gained from the present study could improve the accuracy of analysis concerning hydrology and hydrogeological models, ground water studies, flood related applications and climate analysis studies.

Neighborhood social capital and crime victimization: comparison of spatial regression analysis and hierarchical regression analysis.

PubMed

Takagi, Daisuke; Ikeda, Ken'ichi; Kawachi, Ichiro

2012-11-01

Crime is an important determinant of public health outcomes, including quality of life, mental well-being, and health behavior. A body of research has documented the association between community social capital and crime victimization. The association between social capital and crime victimization has been examined at multiple levels of spatial aggregation, ranging from entire countries, to states, metropolitan areas, counties, and neighborhoods. In multilevel analysis, the spatial boundaries at level 2 are most often drawn from administrative boundaries (e.g., Census tracts in the U.S.). One problem with adopting administrative definitions of neighborhoods is that it ignores spatial spillover. We conducted a study of social capital and crime victimization in one ward of Tokyo city, using a spatial Durbin model with an inverse-distance weighting matrix that assigned each respondent a unique level of "exposure" to social capital based on all other residents' perceptions. The study is based on a postal questionnaire sent to 20-69 years old residents of Arakawa Ward, Tokyo. The response rate was 43.7%. We examined the contextual influence of generalized trust, perceptions of reciprocity, two types of social network variables, as well as two principal components of social capital (constructed from the above four variables). Our outcome measure was self-reported crime victimization in the last five years. In the spatial Durbin model, we found that neighborhood generalized trust, reciprocity, supportive networks and two principal components of social capital were each inversely associated with crime victimization. By contrast, a multilevel regression performed with the same data (using administrative neighborhood boundaries) found generally null associations between neighborhood social capital and crime. Spatial regression methods may be more appropriate for investigating the contextual influence of social capital in homogeneous cultural settings such as Japan. Copyright © 2012 Elsevier Ltd. All rights reserved.

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

PubMed

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

2015-07-21

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

Design and implementation of spatial knowledge grid for integrated spatial analysis

NASA Astrophysics Data System (ADS)

Liu, Xiangnan; Guan, Li; Wang, Ping

2006-10-01

Supported by spatial information grid(SIG), the spatial knowledge grid (SKG) for integrated spatial analysis utilizes the middleware technology in constructing the spatial information grid computation environment and spatial information service system, develops spatial entity oriented spatial data organization technology, carries out the profound computation of the spatial structure and spatial process pattern on the basis of Grid GIS infrastructure, spatial data grid and spatial information grid (specialized definition). At the same time, it realizes the complex spatial pattern expression and the spatial function process simulation by taking the spatial intelligent agent as the core to establish space initiative computation. Moreover through the establishment of virtual geographical environment with man-machine interactivity and blending, complex spatial modeling, network cooperation work and spatial community decision knowledge driven are achieved. The framework of SKG is discussed systematically in this paper. Its implement flow and the key technology with examples of overlay analysis are proposed as well.

Selecting landing sites for lunar lander missions using spatial analysis

NASA Astrophysics Data System (ADS)

Djachkova, Maia; Lazarev, Evgeniy

Russian Federal Space Agency (Roscosmos) is planning to launch two spacecrafts to the Moon with lander missions in 2015 and 2017. [1] Here, we present an approach to create a method of landing sites selection. We researched the physical features of the Moon using spatial analysis techniques presented in ArcGIS Desktop Software in accordance with its suitability for automatic landing. Hence we analyzed Russian lunar program and received the technical characteristics of the spacecrafts and scientific goals that they should meet [1]. Thus we identified the criteria of surface suitability for landing. We divided them into two groups: scientific criteria (the hydrogen content of the regolith [2] and day and night sur-face temperature [3]) and safety criteria (surface slopes and roughness, sky view factor, the Earth altitude, presence of polar permanently shadowed regions). In conformity with some investigations it is believed that the south polar region of the Moon is the most promising territory where water ice can be found (finding water ice is the main goal for Russian lunar missions [1]). According to the selected criteria and selected area of research we used remote sensing data from LRO (Lunar Reconnaissance Orbiter) [4] as basic data, because it is the most actual and easily available. The data was processed and analyzed using spatial analysis techniques of ArcGIS Desktop Software, so we created a number of maps depicting the criteria and then combined and overlaid them. As a result of overlay process we received five territories where the landing will be safe and the scientific goals will have being met. It should be noted that our analysis is only the first order assessment and the results cannot be used as actual landing sites for the lunar missions in 2015 and 2017, since a number of factors, which can only be analyzed in a very large scale, was not taken into account. However, an area of researching is narrowed to five territories, what can make the future research much easier. The analysis of these five areas in a large scale will be the subject of further research. References: [1] Mitrofanov I. G. et al. (2011) LPS XLII, Abstract #1798 [2] Mitrofanov I. G., et al. Hydrogen Mapping of the Lunar South Pole Using the LRO Neutron Detector Experiment LEND // Science vol. 330 2010, pp. 483-486 [3] Paige D.A. et al. (2011) LPS XLII, Abstract #2544 [4] Zuber M.T. et al. (2010) Space Sci. Rev., 150, 63-80

Spatio-Temporal Gap Analysis of OBIS-SEAMAP Project Data: Assessment and Way Forward

PubMed Central

Kot, Connie Y.; Fujioka, Ei; Hazen, Lucie J.; Best, Benjamin D.; Read, Andrew J.; Halpin, Patrick N.

2010-01-01

The OBIS-SEAMAP project has acquired and served high-quality marine mammal, seabird, and sea turtle data to the public since its inception in 2002. As data accumulated, spatial and temporal biases resulted and a comprehensive gap analysis was needed in order to assess coverage to direct data acquisition for the OBIS-SEAMAP project and for taxa researchers should true gaps in knowledge exist. All datasets published on OBIS-SEAMAP up to February 2009 were summarized spatially and temporally. Seabirds comprised the greatest number of records, compared to the other two taxa, and most records were from shipboard surveys, compared to the other three platforms. Many of the point observations and polyline tracklines were located in northern and central Atlantic and the northeastern and central-eastern Pacific. The Southern Hemisphere generally had the lowest representation of data, with the least number of records in the southern Atlantic and western Pacific regions. Temporally, records of observations for all taxa were the lowest in fall although the number of animals sighted was lowest in the winter. Oceanographic coverage of observations varied by platform for each taxa, which showed that using two or more platforms represented habitat ranges better than using only one alone. Accessible and published datasets not already incorporated do exist within spatial and temporal gaps identified. Other related open-source data portals also contain data that fill gaps, emphasizing the importance of dedicated data exchange. Temporal and spatial gaps were mostly a result of data acquisition effort, development of regional partnerships and collaborations, and ease of field data collection. Future directions should include fostering partnerships with researchers in the Southern Hemisphere while targeting datasets containing species with limited representation. These results can facilitate prioritizing datasets needed to be represented and for planning research for true gaps in space and time. PMID:20886047

Spatio-temporal gap analysis of OBIS-SEAMAP project data: assessment and way forward.

PubMed

Kot, Connie Y; Fujioka, Ei; Hazen, Lucie J; Best, Benjamin D; Read, Andrew J; Halpin, Patrick N

2010-09-24

The OBIS-SEAMAP project has acquired and served high-quality marine mammal, seabird, and sea turtle data to the public since its inception in 2002. As data accumulated, spatial and temporal biases resulted and a comprehensive gap analysis was needed in order to assess coverage to direct data acquisition for the OBIS-SEAMAP project and for taxa researchers should true gaps in knowledge exist. All datasets published on OBIS-SEAMAP up to February 2009 were summarized spatially and temporally. Seabirds comprised the greatest number of records, compared to the other two taxa, and most records were from shipboard surveys, compared to the other three platforms. Many of the point observations and polyline tracklines were located in northern and central Atlantic and the northeastern and central-eastern Pacific. The Southern Hemisphere generally had the lowest representation of data, with the least number of records in the southern Atlantic and western Pacific regions. Temporally, records of observations for all taxa were the lowest in fall although the number of animals sighted was lowest in the winter. Oceanographic coverage of observations varied by platform for each taxa, which showed that using two or more platforms represented habitat ranges better than using only one alone. Accessible and published datasets not already incorporated do exist within spatial and temporal gaps identified. Other related open-source data portals also contain data that fill gaps, emphasizing the importance of dedicated data exchange. Temporal and spatial gaps were mostly a result of data acquisition effort, development of regional partnerships and collaborations, and ease of field data collection. Future directions should include fostering partnerships with researchers in the Southern Hemisphere while targeting datasets containing species with limited representation. These results can facilitate prioritizing datasets needed to be represented and for planning research for true gaps in space and time.

Analysis of the changes in the tarcrete layer on the desert surface of Kuwait using satellite imagery and cell-based modeling

NASA Astrophysics Data System (ADS)

Al-Doasari, Ahmad E.

The 1991 Gulf War caused massive environmental damage in Kuwait. Deposition of oil and soot droplets from hundreds of burning oil-wells created a layer of tarcrete on the desert surface covering over 900 km2. This research investigates the spatial change in the tarcrete extent from 1991 to 1998 using Landsat Thematic Mapper (TM) imagery and statistical modeling techniques. The pixel structure of TM data allows the spatial analysis of the change in tarcrete extent to be conducted at the pixel (cell) level within a geographical information system (GIS). There are two components to this research. The first is a comparison of three remote sensing classification techniques used to map the tarcrete layer. The second is a spatial-temporal analysis and simulation of tarcrete changes through time. The analysis focuses on an area of 389 km2 located south of the Al-Burgan oil field. Five TM images acquired in 1991, 1993, 1994, 1995, and 1998 were geometrically and atmospherically corrected. These images were classified into six classes: oil lakes; heavy, intermediate, light, and traces of tarcrete; and sand. The classification methods tested were unsupervised, supervised, and neural network supervised (fuzzy ARTMAP). Field data of tarcrete characteristics were collected to support the classification process and to evaluate the classification accuracies. Overall, the neural network method is more accurate (60 percent) than the other two methods; both the unsupervised and the supervised classification accuracy assessments resulted in 46 percent accuracy. The five classifications were used in a lagged autologistic model to analyze the spatial changes of the tarcrete through time. The autologistic model correctly identified overall tarcrete contraction between 1991--1993 and 1995--1998. However, tarcrete contraction between 1993--1994 and 1994--1995 was less well marked, in part because of classification errors in the maps from these time periods. Initial simulations of tarcrete contraction with a cellular automaton model were not very successful. However, more accurate classifications could improve the simulations. This study illustrates how an empirical investigation using satellite images, field data, GIS, and spatial statistics can simulate dynamic land-cover change through the use of a discrete statistical and cellular automaton model.

Reconstruction of climate in China during 17th-19th centuries using Chinese chronological records

NASA Astrophysics Data System (ADS)

Wang, Pao; Lin, Kuan-Hui; Liao, Yi-Chun; Lee, Shih-Yu; Liao, Hsiung-Ming; Pai, Pi-Ling; Fan, I.-Chun

2017-04-01

Chinese historical documents are an extremely useful source from which much climate information can be retrieved if treated carefully. This is especially relevant to the reconstruction of climate in East Asia in the last 2000 years as the Chinese has kept official chronicles since 500BC and China also represents a large portion of East Asia's land. In addition, there are also local records in many cities and counties. When available, such documentary sources are often superior to environmental proxy data, especially in the time resolution as they usually provide at least annual resolution and even as high as daily records in some cases. This research will report on our recent advances on using a new REACHS dataset that collects primarily documented meteorological records from thousands of imperial and local chronicles in the Chinese history for more than 2000 years. The meteorological records were digitized and coded in the relational database management system in which accurate time (from yearly to daily), space (from province to city/county) and event (from meteorological to phonological and social) information is carefully reserved for analysis. We then formed digital climate series and performed time series and spatial analysis on them to obtain their temporal and spatial characteristics. Our present research results on the annual and seasonal temperature reconstruction during 17th-19th indicates lower temperature in the 17th century. There were also strangely high occurrence frequency of summer snowfall records in the lower reaches of Yangtze River during the Maunder Minimum. Reconstructed precipitation series fluctuated with strong regional character in the Northeast, Central-east and Southeast China. Spectral analysis shows that precipitation series have significant periodicity of 3-5 and 8-12 years during the period, suggesting strong interannual variability and different regional signatures. Flood happened frequently but long lasting drought was more frequently occurred in the 17th than in the following century. Furthermore drought is highly correlated with locust records, especially in the 17th century. The temporal and spatial variability of the climate reconstruction implies hierarchical and multi-scaled climate variability and a likely changing regime of monsoon: its spatial distribution, pattern and intensity. More detailed spatial-temporal analysis will be applied to analyze the dynamism.

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.

Environmental assessment of spatial plan policies through land use scenarios

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

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

2012-01-15

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

Mosaics of Change: Cross-Scale Forest Cover Dynamics and Drivers in Tibetan Yunnan, China

NASA Astrophysics Data System (ADS)

Van Den Hoek, Jamon

In reaction to devastating floods on the Yangtze River in the summer of 1998, the Chinese Central Government introduced a logging ban as part of the Natural Forest Protection Program (NFPP) with the goal of dramatically increasing national forest cover. Since then, over 11 billion USD has been allocated to the program, but the NFPP's success at promoting reforestation is unclear as neither the extent of forest cover change, nor the potential factors influencing the spatial variability of change have been examined. This research employs a case study in northwest Yunnan Province, southwest China, to evaluate the spatial variability of forest cover change under the NFPP and investigate drivers that have influenced recent patterns of change. I employ a mixed methods, cross-scale research framework that includes the analysis of areal trajectories and spatial variability of Landsat-5 imagery-derived forest cover change at three administrative levels before and after the NFPP's introduction; landscape ecology-based metrics to measure the shifting patterns of forest cover change at the patch level; and household interview data on village-level forest resource use patterns and processes in three neighboring villages. Prefecture- and county-level analyses suggest rather stable forest cover across the three-county study area since the introduction of the ban, though township-level measures of forest cover change show a degree of spatial variability as well as a temporal delay in policy implementation effectiveness. Village-level remote sensing analysis shows comparable amounts of forest cover change between study villages but disparate forest resource use patterns in terms of location and amount. Though all research villages continue to exploit local forests for firewood and timber relatively unfettered by policy restrictions, villagers with tourism-derived income are able to buy forest products collected in outside forests much more often; this redistributes local-scale deforestation to the benefit of local and detriment of distant forests. Tourism is often heralded as the solution to rural development challenges in China's southwest, but this research shows the unintended consequences that may result from inconsistent participation at the village-level, consequences which merely redirect, not reduce, forest use pressures, and that are contrary to the goals of state policy.

Photogrammetry and remote sensing for visualization of spatial data in a virtual reality environment

NASA Astrophysics Data System (ADS)

Bhagawati, Dwipen

2001-07-01

Researchers in many disciplines have started using the tool of Virtual Reality (VR) to gain new insights into problems in their respective disciplines. Recent advances in computer graphics, software and hardware technologies have created many opportunities for VR systems, advanced scientific and engineering applications being among them. In Geometronics, generally photogrammetry and remote sensing are used for management of spatial data inventory. VR technology can be suitably used for management of spatial data inventory. This research demonstrates usefulness of VR technology for inventory management by taking the roadside features as a case study. Management of roadside feature inventory involves positioning and visualization of the features. This research has developed a methodology to demonstrate how photogrammetric principles can be used to position the features using the video-logging images and GPS camera positioning and how image analysis can help produce appropriate texture for building the VR, which then can be visualized in a Cave Augmented Virtual Environment (CAVE). VR modeling was implemented in two stages to demonstrate the different approaches for modeling the VR scene. A simulated highway scene was implemented with the brute force approach, while modeling software was used to model the real world scene using feature positions produced in this research. The first approach demonstrates an implementation of the scene by writing C++ codes to include a multi-level wand menu for interaction with the scene that enables the user to interact with the scene. The interactions include editing the features inside the CAVE display, navigating inside the scene, and performing limited geographic analysis. The second approach demonstrates creation of a VR scene for a real roadway environment using feature positions determined in this research. The scene looks realistic with textures from the real site mapped on to the geometry of the scene. Remote sensing and digital image processing techniques were used for texturing the roadway features in this scene.

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

NASA Astrophysics Data System (ADS)

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

2018-07-01

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

Data registration and integration requirements for severe storms research

NASA Technical Reports Server (NTRS)

Dalton, J. T.

1982-01-01

Severe storms research is characterized by temporal scales ranging from minutes (for thunderstorms and tornadoes) to hours (for hurricanes and extra-tropical cyclones). Spatial scales range from tens to hundreds of kilometers. Sources of observational data include a variety of ground based and satellite systems. Requirements for registration and intercomparison of data from these various sources are examined and the potential for operational forecasting application of techniques resulting from the research is discussed. The sensor characteristics and processing procedures relating to the overlay and integrated analysis of satellite and surface observations for severe storms research are reviewed.

Examining the roles that changing harvested areas, closing yield-gaps, and increasing yield ceilings have had on crop production

NASA Astrophysics Data System (ADS)

Johnston, M.; Ray, D. K.; Mueller, N. D.; Foley, J. A.

2011-12-01

With an increasing and increasingly affluent population, there has been tremendous effort to examine strategies for sustainably increasing agricultural production to meet this surging global demand. Before developing new solutions from scratch, though, we believe it is important to consult our recent agricultural history to see where and how agricultural production changes have already taken place. By utilizing the newly created temporal M3 cropland datasets, we can for the first time examine gridded agricultural yields and area, both spatially and temporally. This research explores the historical drivers of agricultural production changes, from 1965-2005. The results will be presented spatially at the global-level (5-min resolution), as well as at the individual country-level. The primary research components of this study are presented below, including the general methodology utilized in each phase and preliminary results for soybean where available. The complete assessment will cover maize, wheat, rice, soybean, and sugarcane, and will include country-specific analysis for over 200 countries, states, territories and protectorates. Phase 1: The first component of our research isolates changes in agricultural production due to variation in planting decisions (harvested area) from changes in production due to intensification efforts (yield). We examine area/yield changes at the pixel-level over 5-year time-steps to determine how much each component has contributed to overall changes in production. Our results include both spatial patterns of changes in production, as well as spatial maps illustrating to what degree the production change is attributed to area and/or yield. Together, these maps illustrate where, why, and by how much agricultural production has changed over time. Phase 2: In the second phase of our research we attempt to determine the impact that area and yield changes have had on agricultural production at the country-level. We calculate a production-weighted result of area and yield contributions for each country, at each time-step. As part of our research we will generate historic figures and tabular data for every country-crop combination. Phase 3: In the final phase of our research, we attempt to demonstrate how different yield performers (for example, those growing crops at the yield floor vs. the yield ceiling) have utilized different area/yield strategies to increase agricultural production. To group individual pixels into performance quintiles, we utilize binning strategies from previous spatial yield-gap assessments. The results from this step will illustrate how the yield ceiling has improved over time vis-à-vis improvements in the yield floor. As we look forward to a more sustainable and productive agricultural future, we hope the results of this global analysis of our agricultural past can be utilized to identify both optimal and adverse strategies for agricultural growth.

GenAlEx 6.5: genetic analysis in Excel. Population genetic software for teaching and research--an update.

PubMed

Peakall, Rod; Smouse, Peter E

2012-10-01

GenAlEx: Genetic Analysis in Excel is a cross-platform package for population genetic analyses that runs within Microsoft Excel. GenAlEx offers analysis of diploid codominant, haploid and binary genetic loci and DNA sequences. Both frequency-based (F-statistics, heterozygosity, HWE, population assignment, relatedness) and distance-based (AMOVA, PCoA, Mantel tests, multivariate spatial autocorrelation) analyses are provided. New features include calculation of new estimators of population structure: G'(ST), G''(ST), Jost's D(est) and F'(ST) through AMOVA, Shannon Information analysis, linkage disequilibrium analysis for biallelic data and novel heterogeneity tests for spatial autocorrelation analysis. Export to more than 30 other data formats is provided. Teaching tutorials and expanded step-by-step output options are included. The comprehensive guide has been fully revised. GenAlEx is written in VBA and provided as a Microsoft Excel Add-in (compatible with Excel 2003, 2007, 2010 on PC; Excel 2004, 2011 on Macintosh). GenAlEx, and supporting documentation and tutorials are freely available at: http://biology.anu.edu.au/GenAlEx. rod.peakall@anu.edu.au.

Psychometric analysis of five measures of spatial ability.

PubMed

Hogan, Thomas P

2012-02-01

This study analyzed psychometric properties of five measures of spatial ability on 96 young adults, with supplementary analysis for three of the measures on another sample of 71 young adults. Two measures were taken from the widely cited Kit of Factor-Referenced Cognitive Tests and three other measures were taken from a relatively new source originally intended as laboratory demonstrations. Previous research provided limited information on the psychometric properties of the measures. All five measures yielded adequate reliability and loaded on a single factor. Three measures yielded markedly skewed distributions. Two measures showed clear sex differences with men scoring higher but this difference seemed contaminated by a speed factor; three measures did not show a sex difference. Recommendations for use of the measures in future studies are provided.

Research on key technology of space laser communication network

NASA Astrophysics Data System (ADS)

Chang, Chengwu; Huang, Huiming; Liu, Hongyang; Gao, Shenghua; Cheng, Liyu

2016-10-01

Since the 21st century, Spatial laser communication has made a breakthrough development. Europe, the United States, Japan and other space powers have carried out the test of spatial laser communication technology on-orbit, and put forward a series of plans. In 2011, China made the first technology demonstration of satellite-ground laser communication carried by HY-2 satellite. Nowadays, in order to improve the transmission rate of spatial network, the topic of spatial laser communication network is becoming a research hotspot at home and abroad. This thesis, from the basic problem of spatial laser communication network to solve, analyzes the main difference between spatial network and ground network, which draws forth the key technology of spatial laser communication backbone network, and systematically introduces our research on aggregation, addressing, architecture of spatial network. From the perspective of technology development status and trends, the thesis proposes the development route of spatial laser communication network in stages. So as to provide reference about the development of spatial laser communication network in China.

Grave mapping in support of the search for missing persons in conflict contexts.

PubMed

Congram, Derek; Kenyhercz, Michael; Green, Arthur Gill

2017-09-01

We review the current and potential uses of Geographic Information Software (GIS) and "spatial thinking" for understanding body disposal behaviour in times of mass fatalities, particularly armed conflict contexts. The review includes observations made by the authors during the course of their academic research and professional consulting on the use of spatial analysis and GIS to support Humanitarian Forensic Action (HFA) to search for the dead, theoretical and statistical considerations in modelling grave site locations, and suggestions on how this work may be advanced further. Copyright © 2017 Elsevier B.V. All rights reserved.

Spatial analysis of health risk assessment with arsenic intake of drinking water in the LanYang plain

NASA Astrophysics Data System (ADS)

Chen, C. F.; Liang, C. P.; Jang, C. S.; Chen, J. S.

2016-12-01

Groundwater is one of the most component water resources in Lanyang plain. The groundwater of the Lanyang Plain contains arsenic levels that exceed the current Taiwan Environmental Protection Administration (Taiwan EPA) limit of 10 μg/L. The arsenic of groundwater in some areas of the Lanyang Plain pose great menace for the safe use of groundwater resources. Therefore, poor water quality can adversely impact drinking water uses, leading to human health risks. This study analyzed the potential health risk associated with the ingestion of arsenic-affected groundwater in the arseniasis-endemic Lanyang plain. Geostatistical approach is widely used in spatial variability analysis and distributions of field data with uncertainty. The estimation of spatial distribution of the arsenic contaminant in groundwater is very important in the health risk assessment. This study used indicator kriging (IK) and ordinary kriging (OK) methods to explore the spatial variability of arsenic-polluted parameters. The estimated difference between IK and OK estimates was compared. The extent of arsenic pollution was spatially determined and the Target cancer risk (TR) and dose response were explored when the ingestion of arsenic in groundwater. Thus, a zonal management plan based on safe groundwater use is formulated. The research findings can provide a plan reference of regional water resources supplies for local government administrators and developing groundwater resources in the Lanyang Plain.

A Behavioral Model of Landscape Change in the Amazon Basin: The Colonist Case

NASA Technical Reports Server (NTRS)

Walker, R. A.; Drzyzga, S. A.; Li, Y. L.; Wi, J. G.; Caldas, M.; Arima, E.; Vergara, D.

2004-01-01

This paper presents the prototype of a predictive model capable of describing both magnitudes of deforestation and its spatial articulation into patterns of forest fragmentation. In a departure from other landscape models, it establishes an explicit behavioral foundation for algorithm development, predicated on notions of the peasant economy and on household production theory. It takes a 'bottom-up' approach, generating the process of land-cover change occurring at lot level together with the geography of a transportation system to describe regional landscape change. In other words, it translates the decentralized decisions of individual households into a collective, spatial impact. In so doing, the model unites the richness of survey research on farm households with the analytical rigor of spatial analysis enabled by geographic information systems (GIs). The paper describes earlier efforts at spatial modeling, provides a critique of the so-called spatially explicit model, and elaborates a behavioral foundation by considering farm practices of colonists in the Amazon basin. It then uses, insight from the behavioral statement to motivate a GIs-based model architecture. The model is implemented for a long-standing colonization frontier in the eastern sector of the basin, along the Trans-Amazon Highway in the State of Para, Brazil. Results are subjected to both sensitivity analysis and error assessment, and suggestions are made about how the model could be improved.

Design & implementation of distributed spatial computing node based on WPS

NASA Astrophysics Data System (ADS)

Liu, Liping; Li, Guoqing; Xie, Jibo

2014-03-01

Currently, the research work of SIG (Spatial Information Grid) technology mostly emphasizes on the spatial data sharing in grid environment, while the importance of spatial computing resources is ignored. In order to implement the sharing and cooperation of spatial computing resources in grid environment, this paper does a systematical research of the key technologies to construct Spatial Computing Node based on the WPS (Web Processing Service) specification by OGC (Open Geospatial Consortium). And a framework of Spatial Computing Node is designed according to the features of spatial computing resources. Finally, a prototype of Spatial Computing Node is implemented and the relevant verification work under the environment is completed.

Temporal and spatial analysis of vegetation coverage changes in Ordos area based on time series GIMMS-NDVI data

NASA Astrophysics Data System (ADS)

Han, Ruimei; Zou, Youfeng; Ma, Chao; Liu, Pei

2014-11-01

Ordos area is the desert-wind erosion desertification steppe transition zone and the complex ecological zone. As the research area, Ordos City has the similar natural geographic environment to ShenDong coalfield. To research its ecological patterns and natural evolution law, it has instructive to reveal temporal and spatial changes of ecological environment with artificial disturbance in western mining. In this paper, a time series of AVHRR-NDVI(Normalized Difference Vegetation Index) data was used to monitor the change of vegetation temporal and spatial dynamics from 1981 to 2006 in Ordos City and ShenDong coalfield, where were as the research area. The MVC (Maximum Value Composites) method, average operation, linear regression, and gradation for NDVI change trend were used to obtained some results, as follows: ¬vegetation coverage had obvious characteristics with periodic change in research area for 26 years, and vegetation growth peak appeared on August, while the lowest appeared on January. The extreme values in Ordos City were 0.2351 and 0.1176, while they were 0.2657 and 0.1272 in ShenDong coalfield. The NDVI value fluctuation was a modest rise trend overall in research area. The extreme values were 0.3071 and 0.1861 in Ordos City, while they were 0.3454 and 0.1904 in ShenDong coalfield. In spatial distribution, slight improvement area and slight degradation area were accounting for 42.49% and 8.37% in Ordos City, while slight improvement area moderate improvement area were accounting for 70.59% and 29.41% in ShenDong coalfield. Above of results indicated there was less vegetation coverage in research area, which reflected the characteristics of fragile natural geographical environment. In addition, vegetation coverage was with a modest rise on the whole, which reflected the natural environment change.

Land Surface Process and Air Quality Research and Applications at MSFC

NASA Technical Reports Server (NTRS)

Quattrochi, Dale; Khan, Maudood

2007-01-01

This viewgraph presentation provides an overview of land surface process and air quality research at MSFC including atmospheric modeling and ongoing research whose objective is to undertake a comprehensive spatiotemporal analysis of the effects of accurate land surface characterization on atmospheric modeling results, and public health applications. Land use maps as well as 10 meter air temperature, surface wind, PBL mean difference heights, NOx, ozone, and O3+NO2 plots as well as spatial growth model outputs are included. Emissions and general air quality modeling are also discussed.

Design Considerations and Research Needs for Expanding the Current Perceptual Model of Spatial Orientation into an In-Cockpit Spatial Disorientation Warning System

DTIC Science & Technology

2016-11-30

USAARL Report No. 2017-07 Design Considerations and Research Needs for Expanding the Current Perceptual Model of Spatial Orientation into an In...Brill5, Angus H. Rupert1 1U.S. Army Aeromedical Research Laboratory 2Laulima Government Solutions, LLC 3National AeroSpace Training and Research ...Center 4Embry-Riddle Aeronautical University 5U.S. Air Force Research Laboratory United States Army Aeromedical Research Laboratory Auditory

Exploring links between juvenile offenders and social disorganization at a large map scale: a Bayesian spatial modeling approach

NASA Astrophysics Data System (ADS)

Law, Jane; Quick, Matthew

2013-01-01

This paper adopts a Bayesian spatial modeling approach to investigate the distribution of young offender residences in York Region, Southern Ontario, Canada, at the census dissemination area level. Few geographic researches have analyzed offender (as opposed to offense) data at a large map scale (i.e., using a relatively small areal unit of analysis) to minimize aggregation effects. Providing context is the social disorganization theory, which hypothesizes that areas with economic deprivation, high population turnover, and high ethnic heterogeneity exhibit social disorganization and are expected to facilitate higher instances of young offenders. Non-spatial and spatial Poisson models indicate that spatial methods are superior to non-spatial models with respect to model fit and that index of ethnic heterogeneity, residential mobility (1 year moving rate), and percentage of residents receiving government transfer payments are, respectively, the most significant explanatory variables related to young offender location. These findings provide overwhelming support for social disorganization theory as it applies to offender location in York Region, Ontario. Targeting areas where prevalence of young offenders could or could not be explained by social disorganization through decomposing the estimated risk map are helpful for dealing with juvenile offenders in the region. Results prompt discussion into geographically targeted police services and young offender placement pertaining to risk of recidivism. We discuss possible reasons for differences and similarities between the previous findings (that analyzed offense data and/or were conducted at a smaller map scale) and our findings, limitations of our study, and practical outcomes of this research from a law enforcement perspective.

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.

Into the environment of mosquito-borne disease: A spatial analysis of vector distribution using traditional and remotely sensed methods

NASA Astrophysics Data System (ADS)

Brown, Heidi E.

Spatially explicit information is increasingly available for infectious disease modeling. However, such information is reluctantly or inappropriately incorporated. My dissertation research uses spatially explicit data to assess relationships between landscape and mosquito species distribution and discusses challenges regarding accurate predictive risk modeling. The goal of my research is to use remotely sensed environmental information and spatial statistical methods to better understand mosquito-borne disease epidemiology for improvement of public health responses. In addition to reviewing the progress of spatial infectious disease modeling, I present four research projects. I begin by evaluating the biases in surveillance data and build up to predictive modeling of mosquito species presence. In the first study I explore how mosquito surveillance trap types influence estimations of mosquito populations. Then. I use county-based human surveillance data and landscape variables to identify risk factors for West Nile virus disease. The third study uses satellite-based vegetation indices to identify spatial variation among West Nile virus vectors in an urban area and relates the variability to virus transmission dynamics. Finally, I explore how information from three satellite sensors of differing spatial and spectral resolution can be used to identify and distinguish mosquito habitat across central Connecticut wetlands. Analyses presented here constitute improvements to the prediction of mosquito distribution and therefore identification of disease risk factors. Current methods for mosquito surveillance data collection are labor intensive and provide an extremely limited, incomplete picture of the species composition and abundance. Human surveillance data offers additional challenges with respect to reporting bias and resolution, but is nonetheless informative in identifying environmental risk factors and disease transmission dynamics. Remotely sensed imagery supports mosquito and human disease surveillance data by providing spatially explicit, line resolution information about environmental factors relevant to vector-borne disease processes. Together, surveillance and remotely sensed environmental data facilitate improved description and modeling of disease transmission. Remote sensing can be used to develop predictive maps of mosquito distribution in relation to disease risk. This has implications for increased accuracy of mosquito control efforts. The projects presented in this dissertation enhance current public health capacities by examining the applications of spatial modeling with respect to mosquito-borne disease.

A fiber-coupled incoherent light source for ultra-precise optical trapping

NASA Astrophysics Data System (ADS)

Menke, Tim; Schittko, Robert; Mazurenko, Anton; Tai, M. Eric; Lukin, Alexander; Rispoli, Matthew; Kaufman, Adam M.; Greiner, Markus

2017-04-01

The ability to engineer arbitrary optical potentials using spatial light modulation has opened up exciting possibilities in ultracold quantum gas experiments. Yet, despite the high trap quality currently achievable, interference-induced distortions caused by scattering along the optical path continue to impede more sensitive measurements. We present a design of a high-power, spatially and temporally incoherent light source that bears the potential to reduce the impact of such distortions. The device is based on an array of non-lasing semiconductor emitters mounted on a single chip whose optical output is coupled into a multi-mode fiber. By populating a large number of fiber modes, the low spatial coherence of the input light is further reduced due to the differing optical path lengths amongst the modes and the short coherence length of the light. In addition to theoretical calculations showcasing the feasibility of this approach, we present experimental measurements verifying the low degree of spatial coherence achievable with such a source, including a detailed analysis of the speckle contrast at the fiber end. We acknowledge support from the National Science Foundation, the Gordon and Betty Moore Foundation's EPiQS Initiative, an Air Force Office of Scientific Research MURI program and an Army Research Office MURI program.

Morphological imaging and quantification of axial xylem tissue in Fraxinus excelsior L. through X-ray micro-computed tomography.

PubMed

Koddenberg, Tim; Militz, Holger

2018-05-05

The popularity of X-ray based imaging methods has continued to increase in research domains. In wood research, X-ray micro-computed tomography (XμCT) is useful for structural studies examining the three-dimensional and complex xylem tissue of trees qualitatively and quantitatively. In this study, XμCT made it possible to visualize and quantify the spatial xylem organization of the angiosperm species Fraxinus excelsior L. on the microscopic level. Through image analysis, it was possible to determine morphological characteristics of the cellular axial tissue (vessel elements, fibers, and axial parenchyma cells) three-dimensionally. X-ray imaging at high resolutions provides very distinct visual insight into the xylem structure. Numerical analyses performed through semi-automatic procedures made it possible to quickly quantify cell characteristics (length, diameter, and volume of cells). Use of various spatial resolutions (0.87-5 μm) revealed boundaries users should be aware of. Nevertheless, our findings, both qualitative and quantitative, demonstrate XμCT to be a valuable tool for studying the spatial cell morphology of F. excelsior. Copyright © 2018. Published by Elsevier Ltd.

Scale dependent inference in landscape genetics

Treesearch

Samuel A. Cushman; Erin L. Landguth

2010-01-01

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

Engineering Genders: A Spatial Analysis of Engineering, Gender, and Learning

ERIC Educational Resources Information Center

Weidler-Lewis, Joanna R.

2016-01-01

This three article dissertation is an investigation into the ontology of learning insofar as learning is a process of becoming. In each article I explore the general questions of who is learning, in what ways, and with what consequences. The context for this research is undergraduate engineering education with particular attention to the…

GENERALIZED TAYLOR-ARIS MOMENT ANALYSIS OF THE TRANSPORT OF SORBING SOLUTES THROUGH POROUS MEDIA WITH SPATIALLY PERIODIC RETARDATION FACTOR. (R825689C037)

EPA Science Inventory

The perspectives, information and conclusions conveyed in research project abstracts, progress reports, final reports, journal abstracts and journal publications convey the viewpoints of the principal investigator and may not represent the views and policies of ORD and EPA. Concl...

Ability Structure and Loss of Vision. Research Series, Number 18.

ERIC Educational Resources Information Center

Juurmaa, Jyrki

In the analysis of ability structure and loss of vision, 228 blind persons (153 male, 75 female) heterogenous in respect to chronological age, sex, degree of blindness, age at onset, and duration, were compared to sighted controls. A test battery was administered which included tests for verbal comprehension, mental arithmetic, spatial ability,…

Commentary: A Summary and Analysis of Twenty-Seven Years of Geoscience Conceptions Research

ERIC Educational Resources Information Center

Cheek, Kim A.

2010-01-01

Seventy-nine studies in geoscience conceptions appeared in peer-reviewed publications in English from 1982 through July 2009. Summaries of the 79 studies suggest certain recurring themes across subject areas: issues with terms, scale (temporal and spatial), role of prior experience, and incorrect application of everyday knowledge to geoscience…

NASA/MSFC FY91 Global Scale Atmospheric Processes Research Program Review

NASA Technical Reports Server (NTRS)

Leslie, Fred W. (Editor)

1991-01-01

The reports presented at the annual Marshall Research Review of Earth Science and Applications are compiled. The following subject areas are covered: understanding of atmospheric processes in a variety of spatial and temporal scales; measurements of geophysical parameters; measurements on a global scale from space; the Mission to Planet Earth Program (comprised of and Earth Observation System and the scientific strategy to analyze these data); and satellite data analysis and fundamental studies of atmospheric dynamics.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010.

PubMed

Zulu, Leo C; Kalipeni, Ezekiel; Johannes, Eliza

2014-05-23

Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi's estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across 'sub-epidemics' while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV "hotspots" clustered among eleven southern districts/cities while a "coldspot" captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale.

Analyzing spatial clustering and the spatiotemporal nature and trends of HIV/AIDS prevalence using GIS: the case of Malawi, 1994-2010

PubMed Central

2014-01-01

Background Although local spatiotemporal analysis can improve understanding of geographic variation of the HIV epidemic, its drivers, and the search for targeted interventions, it is limited in sub-Saharan Africa. Despite recent declines, Malawi’s estimated 10.0% HIV prevalence (2011) remained among the highest globally. Using data on pregnant women in Malawi, this study 1) examines spatiotemporal trends in HIV prevalence 1994-2010, and 2) for 2010, identifies and maps the spatial variation/clustering of factors associated with HIV prevalence at district level. Methods Inverse distance weighting was used within ArcGIS Geographic Information Systems (GIS) software to generate continuous surfaces of HIV prevalence from point data (1994, 1996, 1999, 2001, 2003, 2005, 2007, and 2010) obtained from surveillance antenatal clinics. From the surfaces prevalence estimates were extracted at district level and the results mapped nationally. Spatial dependency (autocorrelation) and clustering of HIV prevalence were also analyzed. Correlation and multiple regression analyses were used to identify factors associated with HIV prevalence for 2010 and their spatial variation/clustering mapped and compared to HIV clustering. Results Analysis revealed wide spatial variation in HIV prevalence at regional, urban/rural, district and sub-district levels. However, prevalence was spatially leveling out within and across ‘sub-epidemics’ while declining significantly after 1999. Prevalence exhibited statistically significant spatial dependence nationally following initial (1995-1999) localized, patchy low/high patterns as the epidemic spread rapidly. Locally, HIV “hotspots” clustered among eleven southern districts/cities while a “coldspot” captured configurations of six central region districts. Preliminary multiple regression of 2010 HIV prevalence produced a model with four significant explanatory factors (adjusted R2 = 0.688): mean distance to main roads, mean travel time to nearest transport, percentage that had taken an HIV test ever, and percentage attaining a senior primary education. Spatial clustering linked some factors to particular subsets of high HIV-prevalence districts. Conclusions Spatial analysis enhanced understanding of local spatiotemporal variation in HIV prevalence, possible underlying factors, and potential for differentiated spatial targeting of interventions. Findings suggest that intervention strategies should also emphasize improved access to health/HIV services, basic education, and syphilis management, particularly in rural hotspot districts, as further research is done on drivers at finer scale. PMID:24886573

Spatial Analysis of Traffic and Routing Path Methods for Tsunami Evacuation

NASA Astrophysics Data System (ADS)

Fakhrurrozi, A.; Sari, A. M.

2018-02-01

Tsunami disaster occurred relatively very fast. Thus, it has a very large-scale impact on both non-material and material aspects. Community evacuation caused mass panic, crowds, and traffic congestion. A further research in spatial based modelling, traffic engineering and splitting zone evacuation simulation is very crucial as an effort to reduce higher losses. This topic covers some information from the previous research. Complex parameters include route selection, destination selection, the spontaneous timing of both the departure of the source and the arrival time to destination and other aspects of the result parameter in various methods. The simulation process and its results, traffic modelling, and routing analysis emphasized discussion which is the closest to real conditions in the tsunami evacuation process. The method that we should highlight is Clearance Time Estimate based on Location Priority in which the computation result is superior to others despite many drawbacks. The study is expected to have input to improve and invent a new method that will be a part of decision support systems for disaster risk reduction of tsunamis disaster.

Resolvent analysis of shear flows using One-Way Navier-Stokes equations

NASA Astrophysics Data System (ADS)

Rigas, Georgios; Schmidt, Oliver; Towne, Aaron; Colonius, Tim

2017-11-01

For three-dimensional flows, questions of stability, receptivity, secondary flows, and coherent structures require the solution of large partial-derivative eigenvalue problems. Reduced-order approximations are thus required for engineering prediction since these problems are often computationally intractable or prohibitively expensive. For spatially slowly evolving flows, such as jets and boundary layers, the One-Way Navier-Stokes (OWNS) equations permit a fast spatial marching procedure that results in a huge reduction in computational cost. Here, an adjoint-based optimization framework is proposed and demonstrated for calculating optimal boundary conditions and optimal volumetric forcing. The corresponding optimal response modes are validated against modes obtained in terms of global resolvent analysis. For laminar base flows, the optimal modes reveal modal and non-modal transition mechanisms. For turbulent base flows, they predict the evolution of coherent structures in a statistical sense. Results from the application of the method to three-dimensional laminar wall-bounded flows and turbulent jets will be presented. This research was supported by the Office of Naval Research (N00014-16-1-2445) and Boeing Company (CT-BA-GTA-1).

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

Advancing the detection of steady-state visual evoked potentials in brain-computer interfaces.

PubMed

Abu-Alqumsan, Mohammad; Peer, Angelika

2016-06-01

Spatial filtering has proved to be a powerful pre-processing step in detection of steady-state visual evoked potentials and boosted typical detection rates both in offline analysis and online SSVEP-based brain-computer interface applications. State-of-the-art detection methods and the spatial filters used thereby share many common foundations as they all build upon the second order statistics of the acquired Electroencephalographic (EEG) data, that is, its spatial autocovariance and cross-covariance with what is assumed to be a pure SSVEP response. The present study aims at highlighting the similarities and differences between these methods. We consider the canonical correlation analysis (CCA) method as a basis for the theoretical and empirical (with real EEG data) analysis of the state-of-the-art detection methods and the spatial filters used thereby. We build upon the findings of this analysis and prior research and propose a new detection method (CVARS) that combines the power of the canonical variates and that of the autoregressive spectral analysis in estimating the signal and noise power levels. We found that the multivariate synchronization index method and the maximum contrast combination method are variations of the CCA method. All three methods were found to provide relatively unreliable detections in low signal-to-noise ratio (SNR) regimes. CVARS and the minimum energy combination methods were found to provide better estimates for different SNR levels. Our theoretical and empirical results demonstrate that the proposed CVARS method outperforms other state-of-the-art detection methods when used in an unsupervised fashion. Furthermore, when used in a supervised fashion, a linear classifier learned from a short training session is able to estimate the hidden user intention, including the idle state (when the user is not attending to any stimulus), rapidly, accurately and reliably.

Avenues for crowd science in Hydrology.

NASA Astrophysics Data System (ADS)

Koch, Julian; Stisen, Simon

2016-04-01

Crowd science describes research that is conducted with the participation of the general public (the crowd) and gives the opportunity to involve the crowd in research design, data collection and analysis. In various fields, scientists have already drawn on underused human resources to advance research at low cost, with high transparency and large acceptance of the public due to the bottom up structure and the participatory process. Within the hydrological sciences, crowd research has quite recently become more established in the form of crowd observatories to generate hydrological data on water quality, precipitation or river flow. These innovative observatories complement more traditional ways of monitoring hydrological data and strengthen a community-based environmental decision making. However, the full potential of crowd science lies in internet based participation of the crowd and it is not yet fully exploited in the field of Hydrology. New avenues that are not primarily based on the outsourcing of labor, but instead capitalize the full potential of human capabilities have to emerge. In multiple realms of solving complex problems, like image detection, optimization tasks, narrowing of possible solutions, humans still remain more effective than computer algorithms. The most successful online crowd science projects Foldit and Galaxy Zoo have proven that the collective of tens of thousands users could clearly outperform traditional computer based science approaches. Our study takes advantage of the well trained human perception to conduct a spatial sensitivity analysis of land-surface variables of a distributed hydrological model to identify the most sensitive spatial inputs. True spatial performance metrics, that quantitatively compare patterns, are not trivial to choose and their applicability is often not universal. On the other hand humans can quickly integrate spatial information at various scales and are therefore a trusted competence. We selected zooniverse, the most popular crowd science platform where over a million registered users contribute to various research projects, to build a survey of the human perception. The survey will be shown during the interactive discussion, but moreover for building future avenues of crowd science in Hydrology the following questions should be discussed: (1) What hydrological problems are suitable for an internet based crowd science application? (2) How to abstract the complex problem to a medium that appeals to the crowd? (3) How to secure good science with reliable results? (4) Can the crowd replace existing and established computer based applications like parameter optimization or forecasting at all?

Spatial Associations and Network Dynamics Between the Vaccine Exemption Dicsussion in Twitter and the Corresponding Geographic Space

NASA Astrophysics Data System (ADS)

Coronado, Alejandra

Recent outbreaks of vaccine-preventable diseases in the United States have drawn attention to the phenomena of vaccine hesitancy and refusal. Hesitancy is seen through the increasing use of exemptions from state vaccine mandates and the recent use of social media for expressing opinions and perspectives related to vaccination. This research places the vaccination narrative into a geographic context and seeks to understand the relationship between vaccine refusal in physical space and the vaccine discussion in cyberspace. Vaccines have long been considered an effective means of eradicating diseases. Recently, however, California has experienced a decline in vaccination rates and an increase in vaccine exemptions. Until the passing of Senate Bill 277 (SB277) in 2015, children were allowed by California law to skip immunizations if a parent submitted a personal beliefs exemption (PBEs). Under SB277, children who are not vaccinated cannot attend school. Some children are still allowed to skip immunizations by submitting a medical exemption (PMEs) at enrollment. Other children are conditionally admitted to school on the 'condition' that they complete any remaining vaccinations when due. This research analyzed the spatial distribution of vaccine exemptions in kindergarten schools in California using the 2015-2016 school immunization data. The two methods used for analysis included Kernel Density Estimation (KDE) and choropleth maps using data aggregated by county. The results from the choropleth maps show that personal belief exemptions for public, private, and charter kindergarten schools are highly concentrated in northern and rural counties. Aggregating vaccine exemptions at the county level and normalizing by school enrollment showed that counties with high ratios of vaccine exemptions vary across public, private, and charter schools. This research also explored the diffusion networks of the vaccine exemption topic in Twitter. Twitter messages related to the California vaccine exemption topic were collected for the whole United States. However, this research only focused on analyzing tweets in California. Two types of information diffusion networks, retweet network and mention network, were examined. This research quantified the influence of users in the networks by applying two network metrics--degree centrality and betweenness centrality. Degree centrality measures the number of connections of a node and is useful to asses which nodes are central for spreading information and influencing others in their immediate neighborhood. Betweenness centrality identifies brokers of information or nodes that connect disparate clusters. Nodes with high betweenness centrality have control over the flow of information in the network. The results suggest that influential users are ranked differently by degree centrality and betweenness centrality for both networks. The results showed that ordinary users may also have strong impacts in the diffusion of information as seen by their high betweenness values despite their low degree centrality. Retweets were found to be more prominent in the diffusion of the vaccine exemption topic compared to mentions. Social network analysis does not capture diffusion processes from a spatial perspective. This research included the spatial context of the mention and retweet networks by using the location information embedded in each node. Nodes were aggregated at the county level and social networks were transformed into visual maps with spatial context. In addition to spatial networks, this research also created chord diagrams to represent the outbound flow and interactions between counties. The findings suggest that county population plays a role in the diffusion of information by social media. Highly populated counties, such as Los Angeles and Sacramento provided a large amount of mention and retweet activity. Additionally, the mention and retweet spatial networks showed counties to have higher in-degree value than out-degree values which indicates more in-flow hubs than out-flow hubs in the network. Unlike the results from the inter-personal social networks, the mention and retweet networks showed that the counties with the highest degree centralities also resulted being the counties with the highest betweenness centrality. Highly populated counties, such as Los Angeles and Sacramento, had very high betweenness centralities in both retweet and mention activity, which means that they served as the bridge and information broker for spreading information related to the vaccine exemption topic. This research is important because most vaccine literature is written from an epidemiological perspective and lacks a geographical component. This research presented an example of applying the spatial social network concept for studying the interaction dynamics between geographic areas. This research expanded studying inter-personal diffusion networks by adding a spatial component. The objective of this research was to study vaccine exemption use and information diffusion across a cyber-physical space in means of better understanding the dynamics of public opinions, views, and responses to the vaccine exemption topic. (Abstract shortened by ProQuest.).

Toolsets for Airborne Data (TAD): Enhanced Airborne Data Merging Functionality through Spatial and Temporal Subsetting

NASA Astrophysics Data System (ADS)

Early, A. B.; Chen, G.; Beach, A. L., III; Northup, E. A.

2016-12-01

NASA has conducted airborne tropospheric chemistry studies for over three decades. These field campaigns have generated a great wealth of observations, including a wide range of the trace gases and aerosol properties. The Atmospheric Science Data Center (ASDC) at NASA Langley Research Center in Hampton Virginia originally developed the Toolsets for Airborne Data (TAD) web application in September 2013 to meet the user community needs for manipulating aircraft data for scientific research on climate change and air quality relevant issues. The analysis of airborne data typically requires data subsetting, which can be challenging and resource intensive for end users. In an effort to streamline this process, the TAD toolset enhancements will include new data subsetting features and updates to the current database model. These will include two subsetters: temporal and spatial, and vertical profile. The temporal and spatial subsetter will allow users to both focus on data from a specific location and/or time period. The vertical profile subsetter will retrieve data collected during an individual aircraft ascent or descent spiral. This effort will allow for the automation of the typically labor-intensive manual data subsetting process, which will provide users with data tailored to their specific research interests. The development of these enhancements will be discussed in this presentation.

Mapping Between Bus Rapid Transit Shelter and High School Location in Semarang

NASA Astrophysics Data System (ADS)

Dewi, D. I. K.; Rakhmatulloh, A. R.; Anggraini, P.

2018-02-01

The main users of public bus transport are those who have the goal to work and attend school. But the last few years there has been a decline in the use of public transport for high school students. Partly of the reason are the high use of motorcycle by student and lack of bus stop service range to high school location. This research has aim to increase the use of public transport for school students by mapping Bus Rapid Transit (BRT) shelter and school locations. The research method used are descriptive quantitative with GIs analysis tools and using spatial analysis approach

Improving 3d Spatial Queries Search: Newfangled Technique of Space Filling Curves in 3d City Modeling

NASA Astrophysics Data System (ADS)

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

2013-09-01

The advantages of three dimensional (3D) city models can be seen in various applications including photogrammetry, urban and regional planning, computer games, etc.. They expand the visualization and analysis capabilities of Geographic Information Systems on cities, and they can be developed using web standards. However, these 3D city models consume much more storage compared to two dimensional (2D) spatial data. They involve extra geometrical and topological information together with semantic data. Without a proper spatial data clustering method and its corresponding spatial data access method, retrieving portions of and especially searching these 3D city models, will not be done optimally. Even though current developments are based on an open data model allotted by the Open Geospatial Consortium (OGC) called CityGML, its XML-based structure makes it challenging to cluster the 3D urban objects. In this research, we propose an opponent data constellation technique of space-filling curves (3D Hilbert curves) for 3D city model data representation. Unlike previous methods, that try to project 3D or n-dimensional data down to 2D or 3D using Principal Component Analysis (PCA) or Hilbert mappings, in this research, we extend the Hilbert space-filling curve to one higher dimension for 3D city model data implementations. The query performance was tested using a CityGML dataset of 1,000 building blocks and the results are presented in this paper. The advantages of implementing space-filling curves in 3D city modeling will improve data retrieval time by means of optimized 3D adjacency, nearest neighbor information and 3D indexing. The Hilbert mapping, which maps a subinterval of the [0, 1] interval to the corresponding portion of the d-dimensional Hilbert's curve, preserves the Lebesgue measure and is Lipschitz continuous. Depending on the applications, several alternatives are possible in order to cluster spatial data together in the third dimension compared to its clustering in 2D.

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-temporal Evolution of Vegetation Coverage and Analysis of it’s Future Trends in Wujiang River Basin

NASA Astrophysics Data System (ADS)

Xiao, Jianyong; Bai, Xiaoyong; Zhou, Dequan; Qian, Qinghuan; Zeng, Cheng; Chen, Fei

2018-01-01

Vegetation coverage dynamics is affected by climatic, topography and human activities, which is an important indicator reflecting the regional ecological environment. Revealing the spatial-temporal characteristics of vegetation coverage is of great significance to the protection and management of ecological environment. Based on MODIS NDVI data and the Maximum Value Composites (MVC), we excluded soil spectrum interference to calculate Fractional Vegetation Coverage (FVC). Then the long-term FVC was used to calculate the spatial pattern and temporal variation of vegetation in Wujiang River Basin from 2000 to 2016 by using Trend analysis and Hurst index. The relationship between topography and spatial distribution of FVC was analyzed. The main conclusions are as follows: (1) The multi-annual mean vegetation coverage reveals a spatial distribution variation characteristic of low value in midstream and high level in other parts of the basin, owing a mean value of 0.6567. (2) From 2000 to 2016, the FVC of the Wujiang River Basin fluctuated between 0.6110 and 0.7380, and the overall growth rate of FVC was 0.0074/a. (3) The area of vegetation coverage tending to improve is more than that going to degrade in the future. Grass land, Arable land and Others improved significantly; karst rocky desertification comprehensive management project lead to persistent vegetation coverage improvement of Grass land, Arable land and Others. Residential land is covered with obviously degraded vegetation, resulting of urban sprawl; (4) The spatial distribution of FVC is positively correlated with TNI. Researches of spatial-temporal evolution of vegetation coverage have significant meaning for the ecological environment protection and management of the Wujiang River Basin.

Influence of the quality of intraoperative fluoroscopic images on the spatial positioning accuracy of a CAOS system.

PubMed

Wang, Junqiang; Wang, Yu; Zhu, Gang; Chen, Xiangqian; Zhao, Xiangrui; Qiao, Huiting; Fan, Yubo

2018-06-01

Spatial positioning accuracy is a key issue in a computer-assisted orthopaedic surgery (CAOS) system. Since intraoperative fluoroscopic images are one of the most important input data to the CAOS system, the quality of these images should have a significant influence on the accuracy of the CAOS system. But the regularities and mechanism of the influence of the quality of intraoperative images on the accuracy of a CAOS system have yet to be studied. Two typical spatial positioning methods - a C-arm calibration-based method and a bi-planar positioning method - are used to study the influence of different image quality parameters, such as resolution, distortion, contrast and signal-to-noise ratio, on positioning accuracy. The error propagation rules of image error in different spatial positioning methods are analyzed by the Monte Carlo method. Correlation analysis showed that resolution and distortion had a significant influence on spatial positioning accuracy. In addition the C-arm calibration-based method was more sensitive to image distortion, while the bi-planar positioning method was more susceptible to image resolution. The image contrast and signal-to-noise ratio have no significant influence on the spatial positioning accuracy. The result of Monte Carlo analysis proved that generally the bi-planar positioning method was more sensitive to image quality than the C-arm calibration-based method. The quality of intraoperative fluoroscopic images is a key issue in the spatial positioning accuracy of a CAOS system. Although the 2 typical positioning methods have very similar mathematical principles, they showed different sensitivities to different image quality parameters. The result of this research may help to create a realistic standard for intraoperative fluoroscopic images for CAOS systems. Copyright © 2018 John Wiley & Sons, Ltd.

Toward critical spatial thinking in the social sciences and humanities.

PubMed

Goodchild, Michael F; Janelle, Donald G

2010-02-01

The integration of geographically referenced information into the conceptual frameworks and applied uses of the social sciences and humanities has been an ongoing process over the past few centuries. It has gained momentum in recent decades with advances in technologies for computation and visualization and with the arrival of new data sources. This article begins with an overview of this transition, and argues that the spatial integration of information resources and the cross-disciplinary sharing of analysis and representation methodologies are important forces for the integration of scientific and artistic expression, and that they draw on core concepts in spatial (and spatio-temporal) thinking. We do not suggest that this is akin to prior concepts of unified knowledge systems, but we do maintain that the boundaries to knowledge transfer are disintegrating and that our abilities in problem solving for purposes of artistic expression and scientific development are enhanced through spatial perspectives. Moreover, approaches to education at all levels must recognize the need to impart proficiency in the critical and efficient application of these fundamental spatial concepts, if students and researchers are to make use of expanding access to a broadening range of spatialized information and data processing technologies.

Geospatial cryptography: enabling researchers to access private, spatially referenced, human subjects data for cancer control and prevention.

PubMed

Jacquez, Geoffrey M; Essex, Aleksander; Curtis, Andrew; Kohler, Betsy; Sherman, Recinda; Emam, Khaled El; Shi, Chen; Kaufmann, Andy; Beale, Linda; Cusick, Thomas; Goldberg, Daniel; Goovaerts, Pierre

2017-07-01

As the volume, accuracy and precision of digital geographic information have increased, concerns regarding individual privacy and confidentiality have come to the forefront. Not only do these challenge a basic tenet underlying the advancement of science by posing substantial obstacles to the sharing of data to validate research results, but they are obstacles to conducting certain research projects in the first place. Geospatial cryptography involves the specification, design, implementation and application of cryptographic techniques to address privacy, confidentiality and security concerns for geographically referenced data. This article defines geospatial cryptography and demonstrates its application in cancer control and surveillance. Four use cases are considered: (1) national-level de-duplication among state or province-based cancer registries; (2) sharing of confidential data across cancer registries to support case aggregation across administrative geographies; (3) secure data linkage; and (4) cancer cluster investigation and surveillance. A secure multi-party system for geospatial cryptography is developed. Solutions under geospatial cryptography are presented and computation time is calculated. As services provided by cancer registries to the research community, de-duplication, case aggregation across administrative geographies and secure data linkage are often time-consuming and in some instances precluded by confidentiality and security concerns. Geospatial cryptography provides secure solutions that hold significant promise for addressing these concerns and for accelerating the pace of research with human subjects data residing in our nation's cancer registries. Pursuit of the research directions posed herein conceivably would lead to a geospatially encrypted geographic information system (GEGIS) designed specifically to promote the sharing and spatial analysis of confidential data. Geospatial cryptography holds substantial promise for accelerating the pace of research with spatially referenced human subjects data.

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

NASA Astrophysics Data System (ADS)

Richardson, Ryan T.

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

Ground and satellite based assessment of meteorological droughts: The Coello river basin case study

NASA Astrophysics Data System (ADS)

Cruz-Roa, A. F.; Olaya-Marín, E. J.; Barrios, M. I.

2017-10-01

The spatial distribution of droughts is a key factor for designing water management policies at basin scale in arid and semi-arid regions. Ground hydro-meteorological data in neo-tropical areas are scarce; therefore, the merging of ground and satellite datasets is a promissory approach for improving our understanding of water distribution. This paper compares three monthly rainfall interpolation methods for drought evaluation. The ordinary kriging technique based on ground data, and cokriging with elevation as auxiliary variable were compared against cokriging using the Tropical Rainfall Measuring Mission (TRMM) Multi-Satellite Precipitation Analysis (TMPA). Twenty rain gauge stations and the 3B42V7 version of the TMPA research dataset were considered. Comparisons were made over the Coello river basin (Colombia) at 3″ spatial resolution covering a period of eight years (1998-2005). The best spatial rainfall estimation was found for cokriging using ground data and elevation. The spatial support of TMPA dataset is very coarse for a merged interpolation with ground data, this spatial scales discrepancy highlight the need to consider scaling rules in the interpolation process.

mapview - Interactive viewing of spatial data in R

NASA Astrophysics Data System (ADS)

Appelhans, Tim; Detsch, Florian; Reudenbach, Cristoph; Woellauer, Stefan

2016-04-01

In this talk we would like to introduce mapview, an R package designed to aid researchers during their work-flow of spatial data analysis. The package was initially developed within the framework of the DFG funded research group "KiLi - Kilimanjaro ecosystems under global change: Linking biodiversity, biotic interactions and biogeochemical ecosystem processes" but has quickly developed into a general purpose spatial data viewer. mapview provides some powerful tools for interactive visualization of standard spatial data in R. It has support for all Spatial*(DataFrame) objects as well as all Raster* objects. It is designed so that one function call - mapview(x) - is all you need to view the data interactively. Adding layers to existing views is very easy and we have taken great care in providing suitable defaults for features such as background maps or coloring but things can be customized flexibly (and permanently) to suit different needs. Even though mapview is for most parts based on the leaflet package, it is far more than just a convenience wrapper around leaflet functionality. mapview provides additional features for handling big data sets (up to several million points) as well as some specialized functionality to view and compare rasters of any size with arbitrary coordinate reference systems. Given that mapview is merely a bridge between R and the underlying leaflet.js javascript library, mapview can be used to produce web-maps by simply providing the path to a designated folder. This talk will be a live demonstration of some of the key features of mapview.

Integrating Hands-On Undergraduate Research in an Applied Spatial Science Senior Level Capstone Course

ERIC Educational Resources Information Center

Kulhavy, David L.; Unger, Daniel R.; Hung, I-Kuai; Douglass, David

2015-01-01

A senior within a spatial science Ecological Planning capstone course designed an undergraduate research project to increase his spatial science expertise and to assess the hands-on instruction methodology employed within the Bachelor of Science in Spatial Science program at Stephen F Austin State University. The height of 30 building features…

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.

A space-time analysis of the WikiLeaks Afghan War Diary: a resource for analyzing the conflict-health nexus.

PubMed

Curtis, Andrew; Ye, Xinyue; Hachey, Kevin; Bourdeaux, Margaret; Norris, Alison

2015-10-16

Although it is widely acknowledged that areas of conflict are associated with a high health burden, from a geospatial perspective it is difficult to establish these patterns at fine scales because of a lack of data. The release of the "WikiLeaks" Afghan War Diary (AWD) provides an interesting opportunity to advance analysis and theory into this interrelationship. This paper will apply two different space time analyses to identify patterns of improvised explosive devices (IED) detonations for the period of 2004 to 2009 in Afghanistan. There is considerable spatial and temporal heterogeneity in IED explosions, with concentrations often following transportation links. The results are framed in terms of a resource for subsequent analyses to other existing health research in Afghanistan. To facilitate this, in our discussion we present a Google Earth file of overlapping rates that can be distributed to any researcher interested in combining his/her fine scale health data with a similarly granular layer of violence. The release of the AWD presents a previously unavailable opportunity to consider how spatially detailed data about violence can be incorporated into understanding, and predicting, health related spillover effects. The AWD can enrich previous research conducted on Afghanistan, and provide a justification for future "official" data sharing at appropriately fine scales.

A Computer Learning Center for Environmental Sciences

NASA Technical Reports Server (NTRS)

Mustard, John F.

2000-01-01

In the fall of 1998, MacMillan Hall opened at Brown University to students. In MacMillan Hall was the new Computer Learning Center, since named the EarthLab which was outfitted with high-end workstations and peripherals primarily focused on the use of remotely sensed and other spatial data in the environmental sciences. The NASA grant we received as part of the "Centers of Excellence in Applications of Remote Sensing to Regional and Global Integrated Environmental Assessments" was the primary source of funds to outfit this learning and research center. Since opening, we have expanded the range of learning and research opportunities and integrated a cross-campus network of disciplines who have come together to learn and use spatial data of all kinds. The EarthLab also forms a core of undergraduate, graduate, and faculty research on environmental problems that draw upon the unique perspective of remotely sensed data. Over the last two years, the Earthlab has been a center for research on the environmental impact of water resource use in and regions, impact of the green revolution on forest cover in India, the design of forest preserves in Vietnam, and detailed assessments of the utility of thermal and hyperspectral data for water quality analysis. It has also been used extensively for local environmental activities, in particular studies on the impact of lead on the health of urban children in Rhode Island. Finally, the EarthLab has also served as a key educational and analysis center for activities related to the Brown University Affiliated Research Center that is devoted to transferring university research to the private sector.

Comparison of environmental and socio-economic domains of vulnerability to flood hazards

NASA Astrophysics Data System (ADS)

Leidel, M.; Kienberger, S.; Lang, S.; Zeil, P.

2009-04-01

Socio-economic and environmental based vulnerability models have been developed within the research context of the FP6 project BRAHMATWINN. The conceptualisation of vulnerability has been defined in the project and is characterised as a function of sensitivity and adaptive capacity, where sensitivity is used to refer to systems that are susceptible to the impacts of environmental stress. Adaptive capacity is used to refer to systems or resources available to communities that could help them adapt or cope with the adverse consequences of environmental stresses in the recovery phase. In a wider context the approach reflects the wider objective and conceptualizations of the IPCC (Intergovernmental Panel on Climate Change) framework, where vulnerability is characterized as a component of overall risk. A methodology has been developed which delineates spatial units of vulnerability (VULNUS). These units share a specific common characteristic and allow the independent spatial modelling of a complex phenomena independent from administrative units and raster based approaches. An increasing detail of spatial data and complex decision problems require flexible means for scaled spatial representations, for mapping the dynamics and constant changes, and delivering the crucial information. Automated techniques of object-based image analysis (OBIA, Lang & Blaschke, 2006), capable of integrating a virtually unlimited set of spatial data sets, try to match the information extraction with our world view. To account for that, a flexible concept of manageable units is required. The term geon was proposed by Lang (2008) to describe generic spatial objects that are homogenous in terms of a varying spatial phenomena under the influence of, and partly controlled by, policy actions. The geon concept acts as a framework for the regionalization of continuous spatial information according to defined parameters of homogeneity. It is flexible in terms of a certain perception of a problem (specific policy realm, specific hazard domain, etc.). In this study, vulnerability units have been derived as a specific instance of a geon set within an area exposed to flood risk. Using geons, we are capable of transforming singular domains of information on specific systemic components to policy-relevant, conditioned information (Kienberger et al., 2008; Tiede & Lang, 2007). According to the work programme socio-economic vulnerabilities have been modelled for the Salzach catchment. A specific set of indicators has been developed with a strong stakeholder orientation. Next to that, and to allow an easier integration within the aimed development of Water Resource Response Units (WRRUs) the environmental domain of vulnerability has additionally been modelled. We present the results of the socio-economic and environmental based approach to model vulnerability. The research methodology utilises census as well as land use/land cover data to derive and assess vulnerability. As a result, spatial units have been identified which represent common characteristics of socio-economic environmental vulnerability. The results show the spatially explicit vulnerability and its underlying components sensitivity and adaptive capacity for socio-economic and environmental domains and discuss differences. Within the test area, the Salzach River catchment in Austria, primarily urban areas adjacent to water courses are highly vulnerable. It can be stated that the delineation of vulnerability units that integrates all dimensions of sustainability are a prerequisite for a holistic and thus adaptive integrated water management approach. Indeed, such units constitute the basis for future dynamic vulnerability assessments, and thus for the assessment of uncertainties due to climate change. Kienberger, S., S. Lang & D. Tiede (2008): Socio-economic vulnerability units - modelling meaningful spatial units. In: Proceedings of the GIS Research UK 16th Annual conference GISRUK 2008, Manchester. Lang, S. (2008): Object-based image analysis for remote sensing applications: modeling reality - dealing with complexity. In: Blaschke, T., S. Lang & G. Hay (eds.): Object-Based Image Analysis - Spatial concepts for knowledge-driven remote sensing applications. New York: Springer, 3-28. Lang, S. & T. Blaschke (2006) Bridging remote sensing and GIS - what are the most supportive pillars? In: S: Lang & T. Blaschke (eds.): International Archives of Photogrammetry, Remote Sensing and Spatial Information Sciences vol. XXXVI-4/C42. CD-ROM and online at www.isprs.org. Tiede D. & S .Lang (2007): Analytical 3D views and virtual globes - putting analytical results into spatial context. ISPRS, ICA, DGfK - Joint Workshop: Visualization and Exploration of Geospatial Data, Stuttgart

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

PubMed

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

2015-01-01

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

Object versus spatial visual mental imagery in patients with schizophrenia

PubMed Central

Aleman, André; de Haan, Edward H.F.; Kahn, René S.

2005-01-01

Objective Recent research has revealed a larger impairment of object perceptual discrimination than of spatial perceptual discrimination in patients with schizophrenia. It has been suggested that mental imagery may share processing systems with perception. We investigated whether patients with schizophrenia would show greater impairment regarding object imagery than spatial imagery. Methods Forty-four patients with schizophrenia and 20 healthy control subjects were tested on a task of object visual mental imagery and on a task of spatial visual mental imagery. Both tasks included a condition in which no imagery was needed for adequate performance, but which was in other respects identical to the imagery condition. This allowed us to adjust for nonspecific differences in individual performance. Results The results revealed a significant difference between patients and controls on the object imagery task (F1,63 = 11.8, p = 0.001) but not on the spatial imagery task (F1,63 = 0.14, p = 0.71). To test for a differential effect, we conducted a 2 (patients v. controls) х 2 (object task v. spatial task) analysis of variance. The interaction term was statistically significant (F1,62 = 5.2, p = 0.026). Conclusions Our findings suggest a differential dysfunction of systems mediating object and spatial visual mental imagery in schizophrenia. PMID:15644999

Changes in tendon spatial frequency parameters with loading.

PubMed

Pearson, Stephen J; Engel, Aaron J; Bashford, Gregory R

2017-05-24

To examine and compare the loading related changes in micro-morphology of the patellar tendon. Fifteen healthy young males (age 19±3yrs, body mass 83±5kg) were utilised in a within subjects matched pairs design. B mode ultrasound images were taken in the sagittal plane of the patellar tendon at rest with the knee at 90° flexion. Repeat images were taken whilst the subjects were carrying out maximal voluntary isometric contractions. Spatial frequency parameters related to the tendon morphology were determined within regions of interest (ROI) from the B mode images at rest and during isometric contractions. A number of spatial parameters were observed to be significantly different between resting and contracted images (Peak spatial frequency radius (PSFR), axis ratio, spatial Q-factor, PSFR amplitude ratio, and the sum). These spatial frequency parameters were indicative of acute alterations in the tendon micro-morphology with loading. Acute loading modifies the micro-morphology of the tendon, as observed via spatial frequency analysis. Further research is warranted to explore its utility with regard to different loading induced micro-morphological alterations, as these could give valuable insight not only to aid strengthening of this tissue but also optimization of recovery from injury and treatment of conditions such as tendinopathies. Copyright © 2017 Elsevier Ltd. All rights reserved.

Spatial problem-solving strategies of middle school students: Wayfinding with geographic information systems

NASA Astrophysics Data System (ADS)

Wigglesworth, John C.

2000-06-01

Geographic Information Systems (GIS) is a powerful computer software package that emphasizes the use of maps and the management of spatially referenced environmental data archived in a systems data base. Professional applications of GIS have been in place since the 1980's, but only recently has GIS gained significant attention in the K--12 classroom. Students using GIS are able to manipulate and query data in order to solve all manners of spatial problems. Very few studies have examined how this technological innovation can support classroom learning. In particular, there has been little research on how experience in using the software correlates with a child's spatial cognition and his/her ability to understand spatial relationships. This study investigates the strategies used by middle school students to solve a wayfinding (route-finding) problem using the ArcView GIS software. The research design combined an individual background questionnaire, results from the Group Assessment of Logical Thinking (GALT) test, and analysis of reflective think-aloud sessions to define the characteristics of the strategies students' used to solve this particular class of spatial problem. Three uniquely different spatial problem solving strategies were identified. Visual/Concrete Wayfinders used a highly visual strategy; Logical/Abstract Wayfinders used GIS software tools to apply a more analytical and systematic approach; Transitional Wayfinders used an approach that showed evidence of one that was shifting from a visual strategy to one that was more analytical. The triangulation of data sources indicates that this progression of wayfinding strategy can be correlated both to Piagetian stages of logical thought and to experience with the use of maps. These findings suggest that GIS teachers must be aware that their students' performance will lie on a continuum that is based on cognitive development, spatial ability, and prior experience with maps. To be most effective, GIS teaching strategies and curriculum development should also represent a progression that correlates to the learners' current skills and experience.

Geostatistical methods in the assessment of the spatial variability of the quality of river water

NASA Astrophysics Data System (ADS)

Krasowska, Małgorzata; Banaszuk, Piotr

2017-11-01

The research was conducted in the agricultural catchment in north-eastern Poland. The aim of this study was to check how geostatistical analysis can be useful for the detection zones and forms of supply stream by water from different sources. The work was included the implementation of hydrochemical profiles. These profiles were made by measuring the electrical conductivity (EC) values and temperature along the river. On the basis of these results, the authors calculated the coefficient of Moran I and performed semivariogram and found that the EC values are correlated on a stretch of about 140 m. This means that the spatial correlation between samples of water in the stream is readable over a distance of about 140 meters. Therefore it is believed that the degree of water mineralization on this section is shaped by water entering the river channel migration in different ways: through tributaries, leachate drainage and surface runoff. In the case of the analyzed catchment, the potential sources of pollution were drainage systems. Therefore, the spatial analysis allowed the identification pollution sources in a catchment, especially in drained agricultural catchments.

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

PubMed

Kumi-Kyereme, Akwasi; Amo-Adjei, Joshua

2013-06-17

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

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

PubMed Central

2013-01-01

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

Spatial analysis of falls in an urban community of Hong Kong

PubMed Central

Lai, Poh C; Low, Chien T; Wong, Martin; Wong, Wing C; Chan, Ming H

2009-01-01

Background Falls are an issue of great public health concern. This study focuses on outdoor falls within an urban community in Hong Kong. Urban environmental hazards are often place-specific and dependent upon the built features, landscape characteristics, and habitual activities. Therefore, falls must be examined with respect to local situations. Results This paper uses spatial analysis methods to map fall occurrences and examine possible environmental attributes of falls in an urban community of Hong Kong. The Nearest neighbour hierarchical (Nnh) and Standard Deviational Ellipse (SDE) techniques can offer additional insights about the circumstances and environmental factors that contribute to falls. The results affirm the multi-factorial nature of falls at specific locations and for selected groups of the population. Conclusion The techniques to detect hot spots of falls yield meaningful results that enable the identification of high risk locations. The combined use of descriptive and spatial analyses can be beneficial to policy makers because different preventive measures can be devised based on the types of environmental risk factors identified. The analyses are also important preludes to establishing research hypotheses for more focused studies. PMID:19291326

Uses of virtual reality for diagnosis, rehabilitation and study of unilateral spatial neglect: review and analysis.

PubMed

Tsirlin, Inna; Dupierrix, Eve; Chokron, Sylvie; Coquillart, Sabine; Ohlmann, Theophile

2009-04-01

Unilateral spatial neglect is a disabling condition frequently occurring after stroke. People with neglect suffer from various spatial deficits in several modalities, which in many cases impair everyday functioning. A successful treatment is yet to be found. Several techniques have been proposed in the last decades, but only a few showed long-lasting effects and none could completely rehabilitate the condition. Diagnostic methods of neglect could be improved as well. The disorder is normally diagnosed with pen-and-paper methods, which generally do not assess patients in everyday tasks and do not address some forms of the disorder. Recently, promising new methods based on virtual reality have emerged. Virtual reality technologies hold great opportunities for the development of effective assessment and treatment techniques for neglect because they provide rich, multimodal, and highly controllable environments. In order to stimulate advancements in this domain, we present a review and an analysis of the current work. We describe past and ongoing research of virtual reality applications for unilateral neglect and discuss the existing problems and new directions for development.

Imaging intratumor heterogeneity: role in therapy response, resistance, and clinical outcome.

PubMed

O'Connor, James P B; Rose, Chris J; Waterton, John C; Carano, Richard A D; Parker, Geoff J M; Jackson, Alan

2015-01-15

Tumors exhibit genomic and phenotypic heterogeneity, which has prognostic significance and may influence response to therapy. Imaging can quantify the spatial variation in architecture and function of individual tumors through quantifying basic biophysical parameters such as CT density or MRI signal relaxation rate; through measurements of blood flow, hypoxia, metabolism, cell death, and other phenotypic features; and through mapping the spatial distribution of biochemical pathways and cell signaling networks using PET, MRI, and other emerging molecular imaging techniques. These methods can establish whether one tumor is more or less heterogeneous than another and can identify subregions with differing biology. In this article, we review the image analysis methods currently used to quantify spatial heterogeneity within tumors. We discuss how analysis of intratumor heterogeneity can provide benefit over more simple biomarkers such as tumor size and average function. We consider how imaging methods can be integrated with genomic and pathology data, instead of being developed in isolation. Finally, we identify the challenges that must be overcome before measurements of intratumoral heterogeneity can be used routinely to guide patient care. ©2014 American Association for Cancer Research.

Applications of geographic information systems (GIS) data and methods in obesity-related research.

PubMed

Jia, P; Cheng, X; Xue, H; Wang, Y

2017-04-01

Geographic information systems (GIS) data/methods offer good promise for public health programs including obesity-related research. This study systematically examined their applications and identified gaps and limitations in current obesity-related research. A systematic search of PubMed for studies published before 20 May 2016, utilizing synonyms for GIS in combination with synonyms for obesity as search terms, identified 121 studies that met our inclusion criteria. We found primary applications of GIS data/methods in obesity-related research included (i) visualization of spatial distribution of obesity and obesity-related phenomena, and basic obesogenic environmental features, and (ii) construction of advanced obesogenic environmental indicators. We found high spatial heterogeneity in obesity prevalence/risk and obesogenic environmental factors. Also, study design and characteristics varied considerably across studies because of lack of established guidance and protocols in the field, which may also have contributed to the mixed findings about environmental impacts on obesity. Existing findings regarding built environment are more robust than those regarding food environment. Applications of GIS data/methods in obesity research are still limited, and related research faces many challenges. More and better GIS data and more friendly analysis methods are needed to expand future GIS applications in obesity-related research. © 2017 World Obesity Federation.

Basic research planning in mathematical pattern recognition and image analysis

NASA Technical Reports Server (NTRS)

Bryant, J.; Guseman, L. F., Jr.

1981-01-01

Fundamental problems encountered while attempting to develop automated techniques for applications of remote sensing are discussed under the following categories: (1) geometric and radiometric preprocessing; (2) spatial, spectral, temporal, syntactic, and ancillary digital image representation; (3) image partitioning, proportion estimation, and error models in object scene interference; (4) parallel processing and image data structures; and (5) continuing studies in polarization; computer architectures and parallel processing; and the applicability of "expert systems" to interactive analysis.

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.

Modeling the effect of spatial policies on ecosystem services and human wellbeing

NASA Astrophysics Data System (ADS)

Geneletti, D.

2012-04-01

Land use conversions rank among the most significant drivers of change in ecosystem services worldwide, affecting human wellbeing and threatening the survival of other species. Hence, predicting the effects of land use decisions on ecosystem services has emerged as a crucial need in land management. Research addressing the link between land use changes and ecosystem services has grown significantly in the last few years, even though it has rarely addressed the tools that most countries use to regulate the development of land: spatial plans. Spatial plans aim at implementing an overall strategy through regulations ("spatial policies") concerning the physical organization of land. The paper presents a methodology aimed at empirically exploring how the implementation of different spatial policies can affect a set of ecosystem services in the future (water purification, soil conservation, habitat for species, carbon sequestration and timber production). Particularly, the study addressed the following three research questions: Q1: What are the effects of different spatial policies on the production of services through time? Q2: How changes in the production affect the actual benefits, hence human wellbeing? Q3: What are the tradeoffs between different ecosystem services and wellbeing constituents, and how are they affected by the spatial scale of analysis? The methodology is based on the generation of land use scenarios that simulate the implementation of different spatial policies through time. For each scenario, the production of key ecosystem services (e.g., water filtration, soil retention) is modeled and compared (Q1). The effects on the constituents of wellbeing (adequate livelihoods, health, etc) are then assessed by looking at spatially-resolved socioeconomic variables that estimate the appropriation of services by different groups of beneficiaries (Q2). Finally, the geographical and temporal patterns of tradeoffs are studied by disaggregating the results at different levels (from regional to sub-municipal) (Q3). The study area is represented by The Araucanía (southern Chile), a region rich in natural resources, but affected by widespread poverty. Conclusions on the potential contribution of the approach to support spatial planning processes are provided.

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

PubMed

Fitterer, Jessica L; Nelson, Trisalyn A

2015-01-01

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

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

PubMed Central

Fitterer, Jessica L.; Nelson, Trisalyn A.

2015-01-01

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

Social Network Analysis of the Irish Biotech Industry: Implications for Digital Ecosystems

NASA Astrophysics Data System (ADS)

van Egeraat, Chris; Curran, Declan

This paper presents an analysis of the socio-spatial structures of innovation, collaboration and knowledge flow among SMEs in the Irish biotech sector. The study applies social network analysis to determine the structure of networks of company directors and inventors in the biotech sector. In addition, the article discusses the implications of the findings for the role and contours of a biotech digital ecosystem. To distil these lessons, the research team organised a seminar which was attended by representatives of biotech actors and experts.

State of the Art of the Landscape Architecture Spatial Data Model from a Geospatial Perspective

NASA Astrophysics Data System (ADS)

Kastuari, A.; Suwardhi, D.; Hanan, H.; Wikantika, K.

2016-10-01

Spatial data and information had been used for some time in planning or landscape design. For a long time, architects were using spatial data in the form of topographic map for their designs. This method is not efficient, and it is also not more accurate than using spatial analysis by utilizing GIS. Architects are sometimes also only accentuating the aesthetical aspect for their design, but not taking landscape process into account which could cause the design could be not suitable for its use and its purpose. Nowadays, GIS role in landscape architecture has been formalized by the emergence of Geodesign terminology that starts in Representation Model and ends in Decision Model. The development of GIS could be seen in several fields of science that now have the urgency to use 3 dimensional GIS, such as in: 3D urban planning, flood modeling, or landscape planning. In this fields, 3 dimensional GIS is able to support the steps in modeling, analysis, management, and integration from related data, that describe the human activities and geophysics phenomena in more realistic way. Also, by applying 3D GIS and geodesign in landscape design, geomorphology information can be better presented and assessed. In some research, it is mentioned that the development of 3D GIS is not established yet, either in its 3D data structure, or in its spatial analysis function. This study literature will able to accommodate those problems by providing information on existing development of 3D GIS for landscape architecture, data modeling, the data accuracy, representation of data that is needed by landscape architecture purpose, specifically in the river area.

Intelligent infrastructure for sustainable potable water: a roundtable for emerging transnational research and technology development needs.

PubMed

Adriaens, Peter; Goovaerts, Pierre; Skerlos, Steven; Edwards, Elizabeth; Egli, Thomas

2003-12-01

Recent commercial and residential development have substantially impacted the fluxes and quality of water that recharge the aquifers and discharges to streams, lakes and wetlands and, ultimately, is recycled for potable use. Whereas the contaminant sources may be varied in scope and composition, these issues of urban water sustainability are of public health concern at all levels of economic development worldwide, and require cheap and innovative environmental sensing capabilities and interactive monitoring networks, as well as tailored distributed water treatment technologies. To address this need, a roundtable was organized to explore the potential role of advances in biotechnology and bioengineering to aid in developing causative relationships between spatial and temporal changes in urbanization patterns and groundwater and surface water quality parameters, and to address aspects of socioeconomic constraints in implementing sustainable exploitation of water resources. An interactive framework for quantitative analysis of the coupling between human and natural systems requires integrating information derived from online and offline point measurements with Geographic Information Systems (GIS)-based remote sensing imagery analysis, groundwater-surface water hydrologic fluxes and water quality data to assess the vulnerability of potable water supplies. Spatially referenced data to inform uncertainty-based dynamic models can be used to rank watershed-specific stressors and receptors to guide researchers and policymakers in the development of targeted sensing and monitoring technologies, as well as tailored control measures for risk mitigation of potable water from microbial and chemical environmental contamination. The enabling technologies encompass: (i) distributed sensing approaches for microbial and chemical contamination (e.g. pathogens, endocrine disruptors); (ii) distributed application-specific, and infrastructure-adaptive water treatment systems; (iii) geostatistical integration of monitoring data and GIS layers; and (iv) systems analysis of microbial and chemical proliferation in distribution systems. This operational framework is aimed at technology implementation while maximizing economic and public health benefits. The outcomes of the roundtable will further research agendas in information technology-based monitoring infrastructure development, integration of processes and spatial analysis, as well as in new educational and training platforms for students, practitioners and regulators. The potential for technology diffusion to emerging economies with limited financial resources is substantial.

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.

Influences of gender role socialization and anxiety on spatial cognitive style.

PubMed

Nori, Raffaella; Mercuri, Noemi; Giusberti, Fiorella; Bensi, Luca; Gambetti, Elisa

2009-01-01

Research on the relationship between personality and social factors in spatial cognitive style is sparse. The present research was conducted to help fill the gap in this domain. We investigated the influence of specific personality traits (masculine/feminine, spatial and trait anxiety), state anxiety, and sex on spatial cognitive style. One hundred forty-two participants completed a battery of spatial tasks in order to assess their spatial cognitive style and filled in questionnaires about the personality traits under examination. Results showed that state anxiety, spatial anxiety, sex, and masculine/feminine trait of personality are predictors of spatial cognitive style. More specifically, it seems that masculine/feminine trait mediates the relationship between sex and spatial cognitive style. Such findings confirm the importance of personality in determining differences in spatial representation.

Spatial variability of detrended soil plow layer penetrometer resistance transect in a sugarcane field

NASA Astrophysics Data System (ADS)

Pérez, Luis D.; Cumbrera, Ramiro; Mato, Juan; Millán, Humberto; Tarquis, Ana M.

2015-04-01

Spatial variability of soil properties is relevant for identifying those zones with physical degradation. In this sense, one has to face the problem of identifying the origin and distribution of spatial variability patterns (Brouder et al., 2001; Millán et al., 2012). The objective of the present work was to quantify the spatial structure of soil penetrometer resistance (PR) collected from a transect data consisted of 221 points equidistant. In each sampling, readings were obtained from 0 cm till 70 cm of depth, with an interval of 5 cm (Pérez, 2012). The study was conducted on a Vertisol (Typic Hapludert) dedicated to sugarcane (Saccharum officinarum L.) production during the last sixty years (Pérez et al., 2010). Recently, scaling approach has been applied on the determination of the scaling data properties (Tarquis et al., 2008; Millán et al., 2012; Pérez, 2012). We focus in the Hurst analysis to characterize the data variability for each depth. Previously a detrended analysis was conducted in order to better study de intrinsic variability of the series. The Hurst exponent (H) for each depth was estimated showing a characteristic pattern and differentiating PR evolution in depth. References Brouder, S., Hofmann, B., Reetz, H.F., 2001. Evaluating spatial variability of soil parameters for input management. Better Crops 85, 8-11. Millán, H; AM Tarquís, Luís D. Pérez, Juan Mato, Mario González-Posada, 2012. Spatial variability patterns of some Vertisol properties at a field scale using standardized data. Soil and Tillage Research, 120, 76-84. Pérez, Luís D. 2012. Influencia de la maquinaria agrícola sobre la variabilidad espacial de la compactación del suelo. Aplicación de la metodología geoestadística-fractal. PhD thesis, UPM (In Spanish). Pérez, Luís D., Humberto Millán, Mario González-Posada 2010. Spatial complexity of soil plow layer penetrometer resistance as influenced by sugarcane harvesting: A prefractal approach. Soil and Tillage Research, 110(1), 77-86. Tarquis, A.M., N. Bird, M.C. Cartagena, A. Whitmore and Y. Pachepsky, 2008. Multiscale entropy-based analyses of soil transect data. Vadose Zone Journal, 7(2), 563-569.

Co-Creating theories and research design for an interdisciplinary project dealing with capacity building for people with migration background in Austria

NASA Astrophysics Data System (ADS)

Weber, Karin; Tscharner, Susanna; Stickler, Therese; Fuchs, Britta; Damyanovic, Doris; Hübl, Johannes

2017-04-01

Understanding spatial and social aspects of vulnerability is of growing importance in the context of climate change and natural hazards. The interplay of structural factors, socio-demographic aspects, current risk communication strategies, spatial planning instruments and related processes and the current spatial and environmental situation, including hazards and hazard zones, geographical locations, building and settlement types, contributing to people`s vulnerabilities needs to be analysed and understood to reduce vulnerability and to foster resilience. The project "CCCapMig" (Climate change and capacity building for people with migration background in Austria) aims at linking spatial and technical, as well as organisational and social aspects of climate change and natural hazards. This paper focuses on the co-creation of the theoretical framework and concepts and outlines the research design for this interdisciplinary cross-analysis of several case studies in rural Austria. The project is designed as an inter- and transdisciplinary survey and brings together engineering sciences, spatial sciences and social sciences. Reflecting the interdisciplinary approach, a theoretical framework was developed that refers to a combination of both theories and frameworks from vulnerability research, theories of risk perception and spatial theories and methods like the Sustainable Livelihoods Framework, the Protection-Motivation Theory and Landscape-Planning Theories: The "Sustainable Livelihoods Framework" adapted (by FA0) for disaster risk management offers an analytical framework to understand the emergence of vulnerabilities from the perspective of people`s livelihoods on individual and community level. It includes human, social, natural, physical and financial aspects and the role of institutions, policies and legal rights in reducing or increasing exposure to disaster risk and coping capacities. Additionally, theories on risk perception, especially Protection-Motivation Theory, developed by social sciences, will be used as assessment frame to understand people`s flood damage mitigation behaviour. Furthermore, spatial theories and landscape planning approaches (like an everyday, evidence-based approach) are combined with theories from social sciences reflecting the interdisciplinary approach of this project that has become standard in studies on disaster and climate change. This theoretical approach was developed through a collaborative research at the beginning of the research design in order to a) develop further and test existing concepts, b) to fine-tune the proposed method setting, c) to foster common understanding of theories and methods within the interdisciplinary research team. In general, the research process is characterised by critical theory and brings in reflective elements, allowing feedback circles between methods and theories. End-users and decision-makers will be integral partners, ensuring that feasibility of the recommendations and guidelines will be guaranteed. Consequently, the methods of data collection in this project reflect the results of the critical discussion of the theoretical frameworks and combine methods of social sciences: interviews with inhabitants living in hazard zones, detailed surveys of families, focus group discussions, and expert interviews with local and regional stakeholders involved in disaster risk management. In addition to that, structural factors, demographic data, current risk communication strategies, legal instruments and related processes and the current spatial and environmental situation (including hazards and hazard zones, geographical locations, building and settlement types) are analysed.

Defense Small Business Innovation Research Program (SBIR). Volume 3. Air Force Abstracts of Phase 1 Awards from FY 1988 SBIR Solicitation

DTIC Science & Technology

1989-05-01

THE TARGET DOPPLER FREQUENCIES. ADAPTIVE SENSORS INC 216 PICO BLVD - STE 8 SANTA MONICA, CA 90405 CONTRACT NUMBER: JOHN S BAILEY TITLE: SPATIALLY...APPLIED RESEARCH ASSOCS INC 4300 SAN MATEO BLVD NE - STE A220 ALBUQUERQUE, NM 87110 CONTRACT NUMBER: FRANK A MAESTAS TITLE: PARAMETRIC ANALYSIS OF EXPLOSIVE...VERIFIED THROUGH SUBSCALE FABRICATION AND TEST. AV DYNAMICS INC 825 MYRTLE AVE MONROVIA, CA 91016 CONTRACT NUMBER: DR P B S LISSAMAN TITLE: LIGHT WEIGHT

Investigation of the Relationship between the Spatial Visualization Success and Visual/Spatial Intelligence Capabilities of Sixth Grade Students

ERIC Educational Resources Information Center

Yenilmez, Kursat; Kakmaci, Ozlem

2015-01-01

The main aim of this research was to examine the relationship between the spatial visualization success and visual/spatial intelligence capabilities of sixth grade students. The sample of the research consists of 1011 sixth grade students who were randomly selected from the primary schools in Eskisehir. In this correlational study, data were…

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

PubMed

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

2009-09-01

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

Structural variations in prefrontal cortex mediate the relationship between early childhood stress and spatial working memory

PubMed Central

Hanson, Jamie L.; Chung, Moo K.; Avants, Brian B.; Rudolph, Karen D.; Shirtcliff, Elizabeth A.; Gee, James C.; Davidson, Richard J.; Pollak, Seth D.

2012-01-01

A large corpus of research indicates exposure to stress impairs cognitive abilities, specifically executive functioning dependent on the prefrontal cortex (PFC). We collected structural MRI scans (n=61), well-validated assessments of executive functioning, and detailed interviews assessing stress exposure in humans, to examine whether cumulative life stress affected brain morphometry and one type of executive functioning, spatial working memory, during adolescence—a critical time of brain development and reorganization. Analysis of variations in brain structure revealed that cumulative life stress and spatial working memory were related to smaller volumes in the PFC, specifically prefrontal gray and white matter between the anterior cingulate and the frontal poles. Mediation analyses revealed that individual differences in prefrontal volumes accounted for the association between cumulative life stress and spatial working memory. These results suggest that structural changes in the PFC may serve as a mediating mechanism through which greater cumulative life stress engenders decrements in cognitive functioning. PMID:22674267

A GIS approach to conducting biogeochemical research in wetlands

NASA Technical Reports Server (NTRS)

Brannon, David P.; Irish, Gary J.

1985-01-01

A project was initiated to develop an environmental data base to address spatial aspects of both biogeochemical cycling and resource management in wetlands. Specific goals are to make regional methane flux estimates and site specific water level predictions based on man controlled water releases within a wetland study area. The project will contribute to the understanding of the Earth's biosphere through its examination of the spatial variability of methane emissions. Although wetlands are thought to be one of the primary sources for release of methane to the atmosphere, little is known about the spatial variability of methane flux. Only through a spatial analysis of methane flux rates and the environmental factors which influence such rates can reliable regional and global methane emissions be calculated. Data will be correlated and studied from Landsat 4 instruments, from a ground survey of water level recorders, precipitation recorders, evaporation pans, and supplemental gauges, and from flood gate water release; and regional methane flux estimates will be made.

Genome-scale modelling of microbial metabolism with temporal and spatial resolution.

PubMed

Henson, Michael A

2015-12-01

Most natural microbial systems have evolved to function in environments with temporal and spatial variations. A major limitation to understanding such complex systems is the lack of mathematical modelling frameworks that connect the genomes of individual species and temporal and spatial variations in the environment to system behaviour. The goal of this review is to introduce the emerging field of spatiotemporal metabolic modelling based on genome-scale reconstructions of microbial metabolism. The extension of flux balance analysis (FBA) to account for both temporal and spatial variations in the environment is termed spatiotemporal FBA (SFBA). Following a brief overview of FBA and its established dynamic extension, the SFBA problem is introduced and recent progress is described. Three case studies are reviewed to illustrate the current state-of-the-art and possible future research directions are outlined. The author posits that SFBA is the next frontier for microbial metabolic modelling and a rapid increase in methods development and system applications is anticipated. © 2015 Authors; published by Portland Press Limited.

Spatial cluster analysis of human cases of Crimean Congo hemorrhagic fever reported in Pakistan.

PubMed

Abbas, Tariq; Younus, Muhammad; Muhammad, Sayyad Aun

2015-01-01

Crimean Congo hemorrhagic fever (CCHF) is a tick-borne viral zoonotic disease that has been reported in almost all geographic regions in Pakistan. The aim of this study was to identify spatial clusters of human cases of CCHF reported in country. Kulldorff's spatial scan statisitc, Anselin's Local Moran's I and Getis Ord Gi* tests were applied on data (i.e. number of laboratory confirmed cases reported from each district during year 2013). The analyses revealed a large multi-district cluster of high CCHF incidence in the uplands of Balochistan province near it border with Afghanistan. The cluster comprised the following districts: Qilla Abdullah; Qilla Saifullah; Loralai, Quetta, Sibi, Chagai, and Mastung. Another cluster was detected in Punjab and included Rawalpindi district and a part of Islamabad. We provide empirical evidence of spatial clustering of human CCHF cases in the country. The districts in the clusters should be given priority in surveillance, control programs, and further research.

The role of egocentric and allocentric abilities in Alzheimer's disease: a systematic review.

PubMed

Serino, Silvia; Cipresso, Pietro; Morganti, Francesca; Riva, Giuseppe

2014-07-01

A great effort has been made to identify crucial cognitive markers that can be used to characterize the cognitive profile of Alzheimer's disease (AD). Because topographical disorientation is one of the earliest clinical manifestation of AD, an increasing number of studies have investigated the spatial deficits in this clinical population. In this systematic review, we specifically focused on experimental studies investigating allocentric and egocentric deficits to understand which spatial cognitive processes are differentially impaired in the different stages of the disease. First, our results highlighted that spatial deficits appear in the earliest stages of the disease. Second, a need for a more ecological assessment of spatial functions will be presented. Third, our analysis suggested that a prevalence of allocentric impairment exists. Specifically, two selected studies underlined that a more specific impairment is found in the translation between the egocentric and allocentric representations. In this perspective, the implications for future research and neurorehabilitative interventions will be discussed. Copyright © 2014 Elsevier B.V. All rights reserved.

Residents' concerns and attitudes toward a municipal solid waste landfill: integrating a questionnaire survey and GIS techniques.

PubMed

Che, Yue; Yang, Kai; Jin, Yan; Zhang, Weiqian; Shang, Zhaoyi; Tai, Jun

2013-12-01

The ever-growing industry of municipal solid waste (MSW) disposal appeals to the growing need for disposal facilities, and MSW treatment facilities are increasingly an environmental and public health concern. Residents living near MSW management facilities are confronted with various risk perceptions, especially odour. In this study, in an effort to assist responsible decision-makers in better planning and managing such a project, a structured questionnaire was designed and distributed to assess the nearby residents' concerns and attitudes surrounding the Laogang Landfill in Shanghai. Geographic information system techniques and relevance analysis were employed to conduct the spatial analysis of physical perceptions, especially odour annoyance. The findings of the research indicate that a significant percentage of the responding sample was aware of the negative impacts of landfills on the environment and public health, and residents in close proximity preferred to live farther from the landfill. The results from the spatial analysis demonstrated a definite degree of correlation between odour annoyance and distance to the facility and proved that the benefits of the socially disadvantaged have been neglected. The research findings also direct attention to the important role of public participation, information disclosure, transparency in management, and mutual communication to avoid conflicts and build social trust.

Spatial aspects of the research on tourist infrastructure with the use of the cartographic method on the basis of Roztoczański National Park

NASA Astrophysics Data System (ADS)

Kałamucki, Krzysztof; Kamińska, Anna; Buk, Dorota

2012-01-01

The aim of the research was to demonstrate changes in tourist trails and in the distribution of tourist infrastructure spots in the area of Roztoczański National Park in its vicinity. Another, equally important aim, was to check the usefulness of tourist infrastructure in both cartographic method of infrastructure research and in cartography of presentation methods. The research covered the region of Roztoczański National Park. The following elements of tourist infrastructure were selected for the analysis: linear elements (walking trails, education paths) and spot elements (accommodation, eating places and the accompanied basis). In order to recreate the state of infrastructure during the last 50 years, it was necessary to analyse the following source material: tourist maps issued as independent publications, maps issued as supplements to tour guides and aerial photography. The information from text sources was used, e.g. from tourist guides, leaflets and monographs. The temporal framework was defined as 50 years from the 1960's until 2009. This time range was divided into five 10-year periods. In order to present the state of tourist infrastructure, its spatial and qualitative changes, 6 maps were produces (maps of states and types of changes). The conducted spatial analyses and the interpretations of maps of states and changes in tourist infrastructure allowed to capture both qualitative and quantitative changes. It was stated that the changes in the trails were not regular. There were parts of trails that did not change for 40 years. There were also some that were constructed during the last decade. Presently, the area is densely covered with tourist trails and education paths. The measurements of lengths of tourist trails and their parts with regard to land cover and category of roads allowed to determine the character of trails and the scope of changes. The conducted analyses proved the usefulness of cartographic methods in researching tourist infrastructure in spatial and quantitative aspects.

Spatial and Temporal Distribution of Tuberculosis in the State of Mexico, Mexico

PubMed Central

Zaragoza Bastida, Adrian; Hernández Tellez, Marivel; Bustamante Montes, Lilia P.; Medina Torres, Imelda; Jaramillo Paniagua, Jaime Nicolás; Mendoza Martínez, Germán David; Ramírez Durán, Ninfa

2012-01-01

Tuberculosis (TB) is one of the oldest human diseases that still affects large population groups. According to the World Health Organization (WHO), there were approximately 9.4 million new cases worldwide in the year 2010. In Mexico, there were 18,848 new cases of TB of all clinical variants in 2010. The identification of clusters in space-time is of great interest in epidemiological studies. The objective of this research was to identify the spatial and temporal distribution of TB during the period 2006–2010 in the State of Mexico, using geographic information system (GIS) and SCAN statistics program. Nine significant clusters (P < 0.05) were identified using spatial and space-time analysis. The conclusion is that TB in the State of Mexico is not randomly distributed but is concentrated in areas close to Mexico City. PMID:22919337

Temporal and spatial patterns in vegetation and atmospheric properties from AVIRIS

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

Roberts, D.A.; Green, R.O.; Adams, J.B.

1997-12-01

Little research has focused on the use of imaging spectrometry for change detection. In this paper, the authors apply Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data to the monitoring of seasonal changes in atmospheric water vapor, liquid water, and surface cover in the vicinity of the Jasper Ridge, CA, for three dates in 1992. Apparent surface reflectance was retrieved and water vapor and liquid water mapped by using a radiative-transfer-based inversion that accounts for spatially variable atmospheres. Spectral mixture analysis (SMA) was used to model reflectance data as mixtures of green vegetation (GV), nonphotosynthetic vegetation (NPV), soil, and shade. Temporal andmore » spatial patterns in endmember fractions and liquid water were compared to the normalized difference vegetation index (NDVI). The reflectance retrieval algorithm was tested by using a temporally invariant target.« less

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

NASA Astrophysics Data System (ADS)

Namysłowska-Wilczyńska, Barbara; Wynalek, Janusz

2017-12-01

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

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.

Preparing the Next Generation of Environmental Scientists to Work at the Frontier of Data-Intensive Research

NASA Astrophysics Data System (ADS)

Hampton, S. E.

2015-12-01

The science necessary to unravel complex environmental problems confronts severe computational challenges - coping with huge volumes of heterogeneous data, spanning vast spatial scales at high resolution, and requiring integration of disparate measurements from multiple disciplines. But as cyberinfrastructure advances to support such work, scientists in many fields lack sufficient computational skills to participate in interdisciplinary, data-intensive research. In response, we developed innovative training workshops for early-career scientists, in order to explore both the needs and solutions for training next-generation scientists in skills for data-intensive environmental research. In 2013 and 2014 we ran intensive 3-week training workshops for early-career researchers. One of the workshops was run concurrently in California and North Carolina, connected by virtual technologies and coordinated schedules. We attracted applicants to the workshop with the opportunity to pursue data-intensive small-group research projects that they proposed. This approach presented a realistic possibility that publishable products could result from 3 weeks of focused hands-on classroom instruction combined with self-directed group research in which instructors were present to assist trainees. Instruction addressed 1) collaboration modes and technologies, 2) data management, preservation, and sharing, 3) preparing data for analysis using scripting, 4) reproducible research, 5) sustainable software practices, 6) data analysis and modeling, and 7) communicating results to broad communities. The most dramatic improvements in technical skills were in data management, version control, and working with spatial data outside of proprietary software. In addition, participants built strong networks and collaborative skills that later resulted in a successful student-led grant proposal, published manuscripts, and participants reported that the training was a highly influential experience.

Spatial analysis of Puerto Rico's terrestrial protected areas [1:240 000

Treesearch

M. Quinones; W.A. Gould; J. Castro-Prieto; S. Martinuzzi

2013-01-01

This research map describes Puerto Rico's terrestrial protected areas based on natural and anthropogenic elements of the landscape. We used geospatial data, i.e., land cover (Gould et al. 2007); urban, suburban, and rural settlements (Martinuzzi et al. 2008); and physiography to illustrate landscape elements and analyze what and how much is protected in Puerto...

Maximum entropy modeling of invasive plants in the forests of Cumberland Plateau and Mountain Region

Treesearch

Dawn Lemke; Philip Hulme; Jennifer Brown; Wubishet. Tadesse

2011-01-01

As anthropogenic influences on the landscape change the composition of 'natural' areas, it is important that we apply spatial technology in active management to mitigate human impact. This research explores the integration of geographic information systems (GIS) and remote sensing with statistical analysis to assist in modeling the distribution of invasive...

Types and Dynamics of Gendered Space: A Case of Emirati Female Learners in a Single-Gender Context

ERIC Educational Resources Information Center

Alzeer, Gergana

2018-01-01

This article is concerned with gendered spaces as they emerge from exploring Emirati female learners' spatiality in a single-gender context. By conducting ethnographic research and utilising Lefebvre's triad of perceived, conceived and lived space for the analysis and categorisation of students' spaces, three types of gendered spaces emerged:…

Indicators of Access to Early Childhood Services in the Mississippi Delta. Rural Early Childhood Report No. 5

ERIC Educational Resources Information Center

Shores, Elizabeth F.; Barbaro, Erin; Barbaro, Michael C.; Flenner, Michelle; Bell, Lynn

2007-01-01

The Early Childhood Atlas facilitates spatial analysis in early childhood services research for the promotion of greater quality and accessibility of early care and education. The Atlas team collects and geocodes federal, state and nongovernmental datasets about early childhood services, integrating selected data elements into its online mapmaking…

A spatial database of wildfires in the United States, 1992-2011

Treesearch

K. C. Short

2014-01-01

The statistical analysis of wildfire activity is a critical component of national wildfire planning, operations, and research in the United States (US). However, there are multiple federal, state, and local entities with wildfire protection and reporting responsibilities in the US, and no single, unified system of wildfire record keeping exists. To conduct even the...

A spatial database of wildfires in the United States, 1992-2011 [Discussions

Treesearch

K. C. Short

2013-01-01

The statistical analysis of wildfire activity is a critical component of national wildfire planning, operations, and research in the United States (US). However, there are multiple federal, state, and local entities with wildfire protection and reporting responsibilities in the US, and no single, unified system of wildfire record-keeping exists. To conduct even the...

Fire metrology: Current and future directions in physics-based measurements

Treesearch

Robert L. Kremens; Alistair M.S. Smith; Matthew B. Dickinson

2010-01-01

The robust evaluation of fire impacts on the biota, soil, and atmosphere requires measurement and analysis methods that can characterize combustion processes across a range of temporal and spatial scales. Numerous challenges are apparent in the literature. These challenges have led to novel research to quantify the 1) structure and heterogeneity of the pre-fire...

Integrating Space with Place in Health Research: A Multilevel Spatial Investigation Using Child Mortality in 1880 Newark, New Jersey

PubMed Central

Xu, Hongwei; Logan, John R.; Short, Susan E.

2014-01-01

Research on neighborhoods and health increasingly acknowledges the need to conceptualize, measure, and model spatial features of social and physical environments. In ignoring underlying spatial dynamics, we run the risk of biased statistical inference and misleading results. In this paper, we propose an integrated multilevel-spatial approach for Poisson models of discrete responses. In an empirical example of child mortality in 1880 Newark, New Jersey, we compare this multilevel-spatial approach with the more typical aspatial multilevel approach. Results indicate that spatially-defined egocentric neighborhoods, or distance-based measures, outperform administrative areal units, such as census units. In addition, although results did not vary by specific definitions of egocentric neighborhoods, they were sensitive to geographic scale and modeling strategy. Overall, our findings confirm that adopting a spatial-multilevel approach enhances our ability to disentangle the effect of space from that of place, and point to the need for more careful spatial thinking in population research on neighborhoods and health. PMID:24763980

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

NASA Astrophysics Data System (ADS)

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

2016-06-01

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

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.

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

PubMed

Monestiez, P; Goulard, M; Charmet, G

1994-04-01

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

Engineering genders: A spatial analysis of engineering, gender, and learning

NASA Astrophysics Data System (ADS)

Weidler-Lewis, Joanna R.

This three article dissertation is an investigation into the ontology of learning insofar as learning is a process of becoming. In each article I explore the general questions of who is learning, in what ways, and with what consequences. The context for this research is undergraduate engineering education with particular attention to the construction of gender in this context. The first article is an examination of the organization of freshman engineering design. The second article draws on Lefebvre's spatial triad as both a theory and method for studying learning. The third article is an interview study of LGBTQA students creating their futures as engineers.

On the Planning and Design of Hospital Circulation Zones.

PubMed

Jiang, Shan; Verderber, Stephen

2017-01-01

This present literature review explores current issues and research inconsistencies regarding the design of hospital circulation zones and the associated health-related outcomes. Large general hospitals are immense, highly sophisticated institutions. Empirical studies have indicated excessively institutional environments in large medical centers are a cause of negative effects to occupants, including stress, anxiety, wayfinding difficulties and spatial disorientation, lack of cognitional control, and stress associated with inadequate access to nature. The rise of patient-centered and evidence-based movements in healthcare planning and design has resulted in a general rise in the quality of hospital physical environments. However, as a core component of any healthcare delivery system, hospital circulation zones have tended to remain neglected within the comparatively broad palette of research conducted and reported to date. A systematic literature review was conducted based upon combinations of key words developed vis-à-vis a literature search in 11 major databases in the realm of the health sciences and the planning and design of built environments for healthcare. Eleven peer-reviewed articles were included in the analysis. Six research themes were identified according to associated health-related outcomes, including wayfinding difficulties and spatial disorientation, communication and socialization patterns, measures and control of excessive noise, patient fall incidents, and occupants' stress and satisfaction levels. Several knowledge gaps as well as commonalities in the pertinent research literature were identified. Perhaps the overriding finding is that occupants' meaningful exposure to views of nature from within hospital circulation zones can potentially enhance wayfinding and spatial navigation. Future research priories on this subject are discussed.

A Spatial Analysis and Game Theoretical Approach Over the Disputed Islands in the Aegean Sea

DTIC Science & Technology

2016-06-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited A SPATIAL ANALYSIS ...REPORT TYPE AND DATES COVERED Master’s thesis 4. TITLE AND SUBTITLE A SPATIAL ANALYSIS AND GAME THEORETICAL APPROACH OVER THE DISPUTED ISLANDS...including perimeter, area, population, distance to Greece, distance to Turkey, and territorial water area. After applying spatial analysis to two

["...cause in such a big hospital ... visually impaired persons like me, alone, can't get anywhere"--the experience of visually impaired people of the in-patient care--an empirical, explorative study].

PubMed

Golde, Christian

2007-02-01

The aim of this study is to explore the experiences of people with visual impairment within in-patient care. Actually, in nursing literature, no similar research is known in the German speaking area. Therefore, an qualitative research framework was used. By using a convenience sampling eight participants have been chosen. Mainly, the thematic content analysis of Burnard has been applied to the analysis of the empirical data. Mental spatial concepts for orientation, primarily acoustically made communicative resonance fields, and Action techniques constitute three major topics, which have been categorised in this study. These concepts are discussed in the cause of the research with respect to their implications on nursing care.

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

PubMed Central

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

2013-01-01

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

CentNet—A deployable 100-station network for surface exchange research

NASA Astrophysics Data System (ADS)

Oncley, S.; Horst, T. W.; Semmer, S.; Militzer, J.; Maclean, G.; Knudson, K.

2014-12-01

Climate, air quality, atmospheric composition, surface hydrology, and ecological processes are directly affected by the Earth's surface. Complexity of this surface exists at multiple spatial scales, which complicates the understanding of these processes. NCAR/EOL currently provides a facility to the research community to make direct eddy-covariance flux observations to quantify surface-atmosphere interactions. However, just as model resolution has continued to increase, there is a need to increase the spatial density of flux measurements to capture the wide variety of scales that contribute to exchange processes close to the surface. NCAR/EOL now has developed the CentNet facility, that is envisioned to have on the order of 100 surface flux stations deployable for periods of months to years. Each station would measure standard meteorological variables, all components of the surface energy balance (including turbulence fluxes and radiation), atmospheric composition, and other quantities to characterize the surface. Thus, CentNet can support observational research in the biogeosciences, hydrology, urban meteorology, basic meteorology, and turbulence. CentNet has been designed to be adaptable to a wide variety of research problems while keeping operations manageable. Tower infrastructure has been designed to be lightweight, easily deployed, and with a minimal set-up footprint. CentNet uses sensor networks to increase spatial sampling at each station. The data system saves every sample on site to retain flexibility in data analysis. We welcome guidance on development and funding priorities as we build CentNet.

Pitfalls and Potentials of Crowd Science: a Meta-Analysis of Contextual Influences

NASA Astrophysics Data System (ADS)

Klippel, A.; Sparks, K.; Wallgrün, J. O.

2015-08-01

Crowd science is becoming an integral part of research in many disciplines. The research discussed in this paper lies at the intersection of spatial and behavioral sciences, two of the greatest beneficiaries of crowd science. As a young methodological development, crowd science needs attention from the perspective of a rigorous evaluation of the data collected to explore potentials as well as limitations (pitfalls). Our research has addressed a variety of contextual effects on the validity of crowdsourced data such as cultural, linguistic, regional, as well as methodological differences that we will discuss here in light of semantics.

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

PubMed

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

2014-11-06

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

Towards Optimal Spectral and Spatial Documentation of Cultural Heritage. Cosch - AN Interdisciplinary Action in the Cost Framework

NASA Astrophysics Data System (ADS)

Boochs, F.; Bentkowska-Kafel, A.; Degringy, C.; Hautta-Kasari, M.; Rizvic, S.; Sitnik, R.; Tremeau, A.

2013-07-01

This paper introduces the aims and early activities of Colour and Space in Cultural Heritage (COSCH), an interdisciplinary European network of experts in the latest optical measuring techniques and electronic imaging applied to documentation of artefacts. COSCH is a forum open to organisations, institutions and companies interested in collaboration within the emerging field of precise spectral and spatial imaging techniques, in physical and chemical sciences applied to cultural heritage objects, as well as in research and applications to conservation and art-historical analysis of such objects. COSCH started in November 2012. Funded by COST, an intergovernmental framework for European Cooperation in Science and Technology, COSCH networking activities enable knowledge exchange and coordination of nationally-funded research on a European level with occasional contribution of experts from other countries. Funding has been made available for four years (2012-2016). Participation is open to researchers across a wide range of disciplines, including computer scientists and museum professionals, art historians and academics in heritage-related fields. COSCH is a trans-domain Action (TD1201) of the COST Domain Materials, Physics and Nanosciences (MPNS) which facilitates and promotes innovation in material science. The work of COSCH is defined in the Memorandum of Understanding between the COST Office and the Chairman of COSCH. The Memorandum is available from http://www.cost.eu/domains_actions/mpns/Actions/TD1201 alongside the latest progress report and other documents. The scientific work draws on earlier and current research of the participants and is organised around the following areas: spectral and spatial object documentation; algorithms and procedures; analysis and restoration of surfaces and objects of material culture; visualisation of cultural heritage objects and its dissemination. Up-to-date information about COSCH activities, including its scientific and training programmes, abstracts of presentations and a list of participants, can all be found on the Action website at http://www.cosch.info.

Methods to achieve accurate projection of regional and global raster databases

USGS Publications Warehouse

Usery, E.L.; Seong, J.C.; Steinwand, D.R.; Finn, M.P.

2002-01-01

This research aims at building a decision support system (DSS) for selecting an optimum projection considering various factors, such as pixel size, areal extent, number of categories, spatial pattern of categories, resampling methods, and error correction methods. Specifically, this research will investigate three goals theoretically and empirically and, using the already developed empirical base of knowledge with these results, develop an expert system for map projection of raster data for regional and global database modeling. The three theoretical goals are as follows: (1) The development of a dynamic projection that adjusts projection formulas for latitude on the basis of raster cell size to maintain equal-sized cells. (2) The investigation of the relationships between the raster representation and the distortion of features, number of categories, and spatial pattern. (3) The development of an error correction and resampling procedure that is based on error analysis of raster projection.

Predicting fecal indicator organism contamination in Oregon coastal streams.

PubMed

Pettus, Paul; Foster, Eugene; Pan, Yangdong

2015-12-01

In this study, we used publicly available GIS layers and statistical tree-based modeling (CART and Random Forest) to predict pathogen indicator counts at a regional scale using 88 spatially explicit landscape predictors and 6657 samples from non-estuarine streams in the Oregon Coast Range. A total of 532 frequently sampled sites were parsed down to 93 pathogen sampling sites to control for spatial and temporal biases. This model's 56.5% explanation of variance, was comparable to other regional models, while still including a large number of variables. Analysis showed the most important predictors on bacteria counts to be: forest and natural riparian zones, cattle related activities, and urban land uses. This research confirmed linkages to anthropogenic activities, with the research prediction mapping showing increased bacteria counts in agricultural and urban land use areas and lower counts with more natural riparian conditions. Copyright © 2015 Elsevier Ltd. All rights reserved.

MALDI Imaging Mass Spectrometry (MALDI-IMS)—Application of Spatial Proteomics for Ovarian Cancer Classification and Diagnosis

PubMed Central

Gustafsson, Johan O. R.; Oehler, Martin K.; Ruszkiewicz, Andrew; McColl, Shaun R.; Hoffmann, Peter

2011-01-01

MALDI imaging mass spectrometry (MALDI-IMS) allows acquisition of mass data for metabolites, lipids, peptides and proteins directly from tissue sections. IMS is typically performed either as a multiple spot profiling experiment to generate tissue specific mass profiles, or a high resolution imaging experiment where relative spatial abundance for potentially hundreds of analytes across virtually any tissue section can be measured. Crucially, imaging can be achieved without prior knowledge of tissue composition and without the use of antibodies. In effect MALDI-IMS allows generation of molecular data which complement and expand upon the information provided by histology including immuno-histochemistry, making its application valuable to both cancer biomarker research and diagnostics. The current state of MALDI-IMS, key biological applications to ovarian cancer research and practical considerations for analysis of peptides and proteins on ovarian tissue are presented in this review. PMID:21340013

MALDI Imaging Mass Spectrometry (MALDI-IMS)-application of spatial proteomics for ovarian cancer classification and diagnosis.

PubMed

Gustafsson, Johan O R; Oehler, Martin K; Ruszkiewicz, Andrew; McColl, Shaun R; Hoffmann, Peter

2011-01-21

MALDI imaging mass spectrometry (MALDI-IMS) allows acquisition of mass data for metabolites, lipids, peptides and proteins directly from tissue sections. IMS is typically performed either as a multiple spot profiling experiment to generate tissue specific mass profiles, or a high resolution imaging experiment where relative spatial abundance for potentially hundreds of analytes across virtually any tissue section can be measured. Crucially, imaging can be achieved without prior knowledge of tissue composition and without the use of antibodies. In effect MALDI-IMS allows generation of molecular data which complement and expand upon the information provided by histology including immuno-histochemistry, making its application valuable to both cancer biomarker research and diagnostics. The current state of MALDI-IMS, key biological applications to ovarian cancer research and practical considerations for analysis of peptides and proteins on ovarian tissue are presented in this review.

Research of Ancient Architectures in Jin-Fen Area Based on GIS&BIM Technology

NASA Astrophysics Data System (ADS)

Jia, Jing; Zheng, Qiuhong; Gao, Huiying; Sun, Hai

2017-05-01

The number of well-preserved ancient buildings located in Shanxi Province, enjoying the absolute maximum proportion of ancient architectures in China, is about 18418, among which, 9053 buildings have the structural style of wood frame. The value of the application of BIM (Building Information Modeling) and GIS (Geographic Information System) is gradually probed and testified in the corresponding fields of ancient architecture’s spatial distribution information management, routine maintenance and special conservation & restoration, the evaluation and simulation of related disasters, such as earthquake. The research objects are ancient architectures in JIN-FEN area, which were first investigated by Sicheng LIANG and recorded in his work of “Chinese ancient architectures survey report”. The research objects, i.e. the ancient architectures in Jin-Fen area include those in Sicheng LIANG’s investigation, and further adjustments were made through authors’ on-site investigation and literature searching & collection. During this research process, the spatial distributing Geodatabase of research objects is established utilizing GIS. The BIM components library for ancient buildings is formed combining on-site investigation data and precedent classic works, such as “Yingzao Fashi”, a treatise on architectural methods in Song Dynasty, “Yongle Encyclopedia” and “Gongcheng Zuofa Zeli”, case collections of engineering practice, by the Ministry of Construction of Qing Dynasty. A building of Guangsheng temple in Hongtong county is selected as an example to elaborate the BIM model construction process based on the BIM components library for ancient buildings. Based on the foregoing work results of spatial distribution data, attribute data of features, 3D graphic information and parametric building information model, the information management system for ancient architectures in Jin-Fen Area, utilizing GIS&BIM technology, could be constructed to support the further research of seismic disaster analysis and seismic performance simulation.

Change of spatial information under rescaling: A case study using multi-resolution image series

NASA Astrophysics Data System (ADS)

Chen, Weirong; Henebry, Geoffrey M.

Spatial structure in imagery depends on a complicated interaction between the observational regime and the types and arrangements of entities within the scene that the image portrays. Although block averaging of pixels has commonly been used to simulate coarser resolution imagery, relatively little attention has been focused on the effects of simple rescaling on spatial structure and the explanation and a possible solution to the problem. Yet, if there are significant differences in spatial variance between rescaled and observed images, it may affect the reliability of retrieved biogeophysical quantities. To investigate these issues, a nested series of high spatial resolution digital imagery was collected at a research site in eastern Nebraska in 2001. An airborne Kodak DCS420IR camera acquired imagery at three altitudes, yielding nominal spatial resolutions ranging from 0.187 m to 1 m. The red and near infrared (NIR) bands of the co-registered image series were normalized using pseudo-invariant features, and the normalized difference vegetation index (NDVI) was calculated. Plots of grain sorghum planted in orthogonal crop row orientations were extracted from the image series. The finest spatial resolution data were then rescaled by averaging blocks of pixels to produce a rescaled image series that closely matched the spatial resolution of the observed image series. Spatial structures of the observed and rescaled image series were characterized using semivariogram analysis. Results for NDVI and its component bands show, as expected, that decreasing spatial resolution leads to decreasing spatial variability and increasing spatial dependence. However, compared to the observed data, the rescaled images contain more persistent spatial structure that exhibits limited variation in both spatial dependence and spatial heterogeneity. Rescaling via simple block averaging fails to consider the effect of scene object shape and extent on spatial information. As the features portrayed by pixels are equally weighted regardless of the shape and extent of the underlying scene objects, the rescaled image retains more of the original spatial information than would occur through direct observation at a coarser sensor spatial resolution. In contrast, for the observed images, due to the effect of the modulation transfer function (MTF) of the imaging system, high frequency features like edges are blurred or lost as the pixel size increases, resulting in greater variation in spatial structure. Successive applications of a low-pass spatial convolution filter are shown to mimic a MTF. Accordingly, it is recommended that such a procedure be applied prior to rescaling by simple block averaging, if insufficient image metadata exist to replicate the net MTF of the imaging system, as might be expected in land cover change analysis studies using historical imagery.

Understanding high magnitude flood risk: evidence from the past

NASA Astrophysics Data System (ADS)

MacDonald, N.

2009-04-01

The average length of gauged river flow records in the UK is ~25 years, which presents a problem in determining flood risk for high-magnitude flood events. Severe floods have been recorded in many UK catchments during the past 10 years, increasing the uncertainty in conventional flood risk estimates based on river flow records. Current uncertainty in flood risk has implications for society (insurance costs), individuals (personal vulnerability) and water resource managers (flood/drought risk). An alternative approach is required which can improve current understanding of the flood frequency/magnitude relationship. Historical documentary accounts are now recognised as a valuable resource when considering the flood frequency/magnitude relationship, but little consideration has been given to the temporal and spatial distribution of these records. Building on previous research based on British rivers (urban centre): Ouse (York), Trent (Nottingham), Tay (Perth), Severn (Shrewsbury), Dee (Chester), Great Ouse (Cambridge), Sussex Ouse (Lewes), Thames (Oxford), Tweed (Kelso) and Tyne (Hexham), this work considers the spatial and temporal distribution of historical flooding. The selected sites provide a network covering many of the largest river catchments in Britain, based on urban centres with long detailed documentary flood histories. The chronologies offer an opportunity to assess long-term patterns of flooding, indirectly determining periods of climatic variability and potentially increased geomorphic activity. This research represents the first coherent large scale analysis undertaken of historical multi-catchment flood chronologies, providing an unparalleled network of sites, permitting analysis of the spatial and temporal distribution of historical flood patterns on a national scale.

Analysis of Spatial Autocorrelation for Optimal Observation Network in Korea

NASA Astrophysics Data System (ADS)

Park, S.; Lee, S.; Lee, E.; Park, S. K.

2016-12-01

Many studies for improving prediction of high-impact weather have been implemented, such as THORPEX (The Observing System Research and Predictability Experiment), FASTEX (Fronts and Atlantic Storm-Track Experiment), NORPEX (North Pacific Experiment), WSR/NOAA (Winter Storm Reconnaissance), and DOTSTAR (Dropwindsonde Observations for Typhoon Surveillance near the TAiwan Region). One of most important objectives in these studies is to find effects of observation on forecast, and to establish optimal observation network. However, there are lack of such studies on Korea, although Korean peninsula exhibits a highly complex terrain so it is difficult to predict its weather phenomena. Through building the future optimal observation network, it is necessary to increase utilization of numerical weather prediction and improve monitoring·tracking·prediction skills of high-impact weather in Korea. Therefore, we will perform preliminary study to understand the spatial scale for an expansion of observation system through Spatial Autocorrelation (SAC) analysis. In additions, we will develop a testbed system to design an optimal observation network. Analysis is conducted with Automatic Weather System (AWS) rainfall data, global upper air grid observation (i.e., temperature, pressure, humidity), Himawari satellite data (i.e., water vapor) during 2013-2015 of Korea. This study will provide a guideline to construct observation network for not only improving weather prediction skill but also cost-effectiveness.

Integrating GIS with AHP and Fuzzy Logic to generate hand, foot and mouth disease hazard zonation (HFMD-HZ) model in Thailand

NASA Astrophysics Data System (ADS)

Samphutthanon, R.; Tripathi, N. K.; Ninsawat, S.; Duboz, R.

2014-12-01

The main objective of this research was the development of an HFMD hazard zonation (HFMD-HZ) model by applying AHP and Fuzzy Logic AHP methodologies for weighting each spatial factor such as disease incidence, socio-economic and physical factors. The outputs of AHP and FAHP were input into a Geographic Information Systems (GIS) process for spatial analysis. 14 criteria were selected for analysis as important factors: disease incidence over 10 years from 2003 to 2012, population density, road density, land use and physical features. The results showed a consistency ratio (CR) value for these main criteria of 0.075427 for AHP, the CR for FAHP results was 0.092436. As both remained below the threshold of 0.1, the CR value were acceptable. After linking to actual geospatial data (disease incidence 2013) through spatial analysis by GIS for validation, the results of the FAHP approach were found to match more accurately than those of the AHP approach. The zones with the highest hazard of HFMD outbreaks were located in two main areas in central Muang Chiang Mai district including suburbs and Muang Chiang Rai district including the vicinity. The produced hazardous maps may be useful for organizing HFMD protection plans.

Drought disaster vulnerability mapping of agricultural sector in Bringin District, Semarang Regency

NASA Astrophysics Data System (ADS)

Lestari, D. R.; Pigawati, B.

2018-02-01

Agriculture sector is a sector that is directly affected by drought. The phenomenon of drought disaster on agriculture sector has occurred in Semarang regency. One of districts in Semarang which is affected by drought is Bringin district. Bringin district is a productive agricultural area. However, the district experienced the most severe drought in 2015. The question research of this study is, “How is the spatial distribution of drought vulnerability on agriculture sector in Bringin district, Semarang regency?” The purpose of this study is to determine the spatial distribution of drought vulnerability on agriculture sector to village units in Bringin district. This study investigated drought vulnerability based on Intergovernmental Panel on Climate Change (IPCC) by analyzing exposure, sensitivity, and adaptive capacity through mapping process. This study used quantitative approach. There were formulation analysis, scoring analysis, and overlay analysis. Drought vulnerability on agriculture sector in Bringin district was divided into three categories: low, medium, and high.

Effect of Variable Spatial Scales on USLE-GIS Computations

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Breast MRI radiogenomics: Current status and research implications.

PubMed

Grimm, Lars J

2016-06-01

Breast magnetic resonance imaging (MRI) radiogenomics is an emerging area of research that has the potential to directly influence clinical practice. Clinical MRI scanners today are capable of providing excellent temporal and spatial resolution, which allows extraction of numerous imaging features via human extraction approaches or complex computer vision algorithms. Meanwhile, advances in breast cancer genetics research has resulted in the identification of promising genes associated with cancer outcomes. In addition, validated genomic signatures have been developed that allow categorization of breast cancers into distinct molecular subtypes as well as predict the risk of cancer recurrence and response to therapy. Current radiogenomics research has been directed towards exploratory analysis of individual genes, understanding tumor biology, and developing imaging surrogates to genetic analysis with the long-term goal of developing a meaningful tool for clinical care. The background of breast MRI radiogenomics research, image feature extraction techniques, approaches to radiogenomics research, and promising areas of investigation are reviewed. J. Magn. Reson. Imaging 2016;43:1269-1278. © 2015 Wiley Periodicals, Inc.

Planning long-term vegetation studies at landscape scales

USGS Publications Warehouse

Stohlgren, Thomas J.

1995-01-01

Long-term ecological research is receiving more attention now than ever before. Two recent books, Long-term Studies in Ecology: Approaches and Alternatives, edited by Gene Likens (1989), and Long-term Ecological Research: An International Perspective, edited by Paul Risser (1991), prompt the question, “Why are these books so thin?” Except for data from paleoecological, retrospective studies (see below), there are exceptionally few long-term data sets in terrestrial ecology (Strayer et al. 1986; Tilman 1989; this volume). In a sample of 749 papers published in Ecology, Tilman (1989) found that only 1.7% of the studies lasted at least five field seasons. Only one chapter in each of the review books dealt specifically with expanding both the temporal and the spatial scales of ecological research (Berkowitz et al. 1989; Magnuson et al. 1991). Judging by the growing number of landscape-scale long-term studies, however, such as the Long-Term Ecological Research (LTER) Program (Callahan 1991), the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program (EMAP; Palmer et al. 1991), the U.S. Army’s Land Condition-Trend Analysis (LCTA) Program (Diersing et al. 1992), and various agencies’ global change research programs (CEES 1993), there is a growing interest to expand ecological research both temporally and spatially.

Preliminary Evaluation of MapReduce for High-Performance Climate Data Analysis

NASA Technical Reports Server (NTRS)

Duffy, Daniel Q.; Schnase, John L.; Thompson, John H.; Freeman, Shawn M.; Clune, Thomas L.

2012-01-01

MapReduce is an approach to high-performance analytics that may be useful to data intensive problems in climate research. It offers an analysis paradigm that uses clusters of computers and combines distributed storage of large data sets with parallel computation. We are particularly interested in the potential of MapReduce to speed up basic operations common to a wide range of analyses. In order to evaluate this potential, we are prototyping a series of canonical MapReduce operations over a test suite of observational and climate simulation datasets. Our initial focus has been on averaging operations over arbitrary spatial and temporal extents within Modern Era Retrospective- Analysis for Research and Applications (MERRA) data. Preliminary results suggest this approach can improve efficiencies within data intensive analytic workflows.