Jürgen Symanzik

Effects of urbanization on the aquatic fauna of the Line Creek watershed, Atlanta—a satellite perspective

Abstract Impervious surface area (ISA) was derived for a period from 1979 to 1997 from Landsat MSS and TM data for the Line Creek watershed that lies to the south of the city of Atlanta, GA. The change in ISA is presented as an ecological indicator to examine the cumulative water resource impacts on mussel population in three sub-watersheds of Line Creek—namely, Line, Flat, and Whitewater creeks. The satellite analysis shows that ISA expansion occurred substantially from 1987 to 1997 and is predominantly in industrial, commercial, and shopping center (ICS) complexes but also in smaller lot-size residential development. Evidence of mussel habitat degradation is indicated and loss of species (in the region of 50 to 70%) is present in areas where ISA expansion is observed—specifically in ICS complex development in and around Peachtree City that drains directly into the Line and Flat creeks. This is in marked contrast to Whitewater Creek where overall development of ISA is less and no major loss of mussel species is observed.

Dynamic graphics in a GIS: more examples using linked software

Abstract This document describes the linking of two software packages to provide exploratory dynamic graphical tools directly from within a geographic information system (GIS). The GIS we have used is ArcView 2.1, which is a widely used package for examining maps and images. XGobi is the dynamic graphics package that is publicly available and also widely used for exploring multivariate data. The link involves cross-referencing each location in the map view provided by ArcView with a multitude of plot types in XGobi. This cross-referencing allows a user to interact with either the map view or the XGobi plots by painting (that is, brushing) groups of points with different colors or glyph (shape) types, identifying points, or erasing them, and have the similar changes made automatically in the other view. Examples of the different types of plots and interactions are given in the paper in both image and video format. ArcView is a registered trademark of Environmental Systems Research Institute, Inc., Redlands, CA, U.S.A.

Geographic Variations in Cardiovascular Health in the United States: Contributions of State‐ and Individual‐Level Factors

Background Improving cardiovascular health (CVH) of all Americans by 2020 is a strategic goal of the American Heart Association. Understanding the sources of variation and identifying contextual factors associated with poor CVH may suggest important avenues for prevention. Methods and Results Cross-sectional data from the Behavioral Risk Factor Surveillance System for the year 2011 were linked to state-level coronary heart disease and stroke mortality data from the National Vital Statistics System and to state-level measures of median household income, income inequality, taxes on soda drinks and cigarettes, and food and physical activity environments from various administrative sources. Poor CVH was defined according to the American Heart Association definition using 7 self-reported CVH metrics (current smoking, physical inactivity, obesity, poor diet, hypertension, diabetes, and high cholesterol). Linked micromap plots and multilevel logistic models were used to examine state variation in poor CVH and to investigate the contributions of individual- and state-level factors to this variation. We found significant state-level variation in the prevalence of poor CVH (median odds ratio 1.32, P<0.001). Higher rates of poor CVH and cardiovascular disease mortality were clustered in the southern states. Minority and low socioeconomic groups were strongly associated with poor CVH and explained 51% of the state-level variation in poor CVH; state-level factors explained an additional 28%. State-level median household income (odds ratio 0.89; 95% CI 0.84–0.94), taxes on soda drinks (odds ratio 0.94; 95% CI 0.89–0.99), farmers markets (odds ratio 0.91; 95% CI 0.85–0.98), and convenience stores (odds ratio 1.09; 95% CI 1.01–1.17) were predictive of poor CVH even after accounting for individual-level factors. Conclusions There is significant state-level variation in poor CVH that is partly explained by individual- and state-level factors. Additional longitudinal research is warranted to examine the influence of state-level policies and food and physical activity environments on poor CVH.

Reliability of hand diagrams for the epidemiologic case definition of carpal tunnel syndrome

The purpose of this study was to evaluate the inter-rater reliability of hand diagrams, which are commonly used in research case definitions of carpal tunnel syndrome (CTS). To evaluate the potential of non-random misclassification of cases, we also studied predictors of rater disagreement as a function of personal and work factors, and of hand symptoms not classic for CTS. Participants in a longitudinal study investigating the development of CTS completed repeated self-administered questionnaires. Three experienced clinicians, blind to subjects’ work or personal history, independently rated all hand diagrams on an ordinal scale from 0 to 3. Disagreements between ratings were resolved by consensus. Reliability was measured by the weighted kappa statistic. Logistic regression models evaluated predictors of disagreement. Three hundred and thirty-three subjects completed 494 hand diagrams. Eighty-five percent were completed by self-administered questionnaire and 15% by telephone interview. Weighted kappa values representing agreement among the three raters, were 0.83 (95% CI: 0.78, 0.87) for right hand diagrams and 0.88 (95% CI: 0.83, 0.91) for left hand diagrams. Ratings from hand diagrams obtained by telephone interview produced better agreement. Agreement among raters was not affected by subjects’ personal or work factors. Disagreement among raters was associated with the presence of hand/wrist symptoms other than classic CTS symptoms. Overall, high levels of agreement were attained by independent raters of hand diagrams. Personal factors did not affect agreement among raters, but presence of non-CTS symptoms seemed to affect results and should be considered in studies focused on diverse populations with heterogeneity of upper extremity symptoms.

Visual clustering and classification: The Oronsay particle size data set revisited

SummaryInteractive statistical graphics can be effectively used to find natural groupings in observations. In this paper we want to demonstrate how clustering and classification can be done with three approaches based on highly interactive graphical environments: high-dimensional scatterplots as available in XGobi, parallel coordinate plots as available in EXPLORN, and linked low-dimensional views as available in MANET. We will point out the strenghts and the weaknesses of these techniques by comparing their behaviour when applied to the Oronsay particle size data set.

Linking ArcView™ and XGobi: Insight behind the Front End

Abstract This article presents aspects of the implementation of a bidirectional link between the Geographic Information System (GIS) ArcView™ and the interactive dynamic statistical graphics program XGobi. We describe the main functionality of the link, the underlying remote procedure call (RPC) mechanism, and internal data structures, and discuss topics such as security, concurrency, and linked brushing. We think that these topics are of particular interest to software authors intending to link similar software packages, and software users learning about strengths (and weaknesses) of the implementation of our link.

Exploring Environmental Data in a Highly Immersive Virtual Reality Environment

Geography inherently fills a 3D space and yet we struggle with displaying geography using, primarily, 2D display devices. Virtual environments offer a more realistically-dimensioned display space and this is being realized in the expanding area of research on 3D Geographic Information Systems (GISs). Traditionally, a GIS has only limited tools for statistical analysis, and 3D GIS research has concentrated on the visualization of the geographical terrain. Here we discuss linking multivariate statistical graphics to geography in the highly immersive C2 virtual reality environment at Iowa State University using mid-Atlantic streams data.

Interactive Linked Micromap Plots for the Display of Geographically Referenced Statistical Data

Over the last decade, researchers have developed many improvements to make statistical graphics more accessible to the general public. These improvements include making statistical summaries more visual and providing more information at the same time. Research in this area involved converting statistical tables into plots (Carr, 1994; Carr and Nusser, 1995), new ways of displaying geographically referenced data (Carr et al., 1992), and, inparticular, the developmentof linkedmicromap(LM)plots, often simply called micromaps (Carr and Pierson, 1996; Carr et al., 1998, 2000a). LM plots, initially called map row plots as well as linked map-attribute graphics, were first presented in a poster session sponsored by the American Statistical Association (ASA) Section on Statistical Graphics at the 1996 Joint Statistical Meetings (Olsen et al., 1996).More details on the history of LMplots and their connection to other research can be found in these early references on micromaps. More recent references on LM plots (Carr et al., 2000b; Carr, 2001) focused on their use for communicating summary data from health and environmental studies.

Some Dynamic Graphics for Spatial Data (with Multiple Attributes) in a GIS

This paper discusses some multivariate exploratory spatial data analysis tools for detecting spatial dependence. The ideas explored are related to canonical correlation analysis and the graphical tools are related to the dynamic method called the grand tour. The work is implemented with a link between a Geographic Information System, ARC/INFOTM, and software for exploring multivariate data, XGobi.

Interactive and Dynamic Graphics

Interactive and dynamic statistical graphics enable data analysts in all fields to carry out visual investigations leading to insights into relationships in complex data. Interactive and dynamic statistical graphics involve methods for viewing data in the form of point clouds or modeled surfaces. Higher-dimensional data can be projected into one-, two- or three-dimensional planes in a set of multiple views or as a continuous sequence of views which constitutes motion through the higher-dimensional space containing the data.