James J. Majure

Spatio-Temporal Statistical Modeling of Livestock Waste in Streams

Livestock agriculture (e.g., dairy, beef, pork, poultry) in the United States is tending rapidly toward operations where a large number of animals are concentrated in a relatively small area. The economies of scale are counterbalanced by the dangers of pollution from inadequate treatment of animal waste. Traditional methods of treatment involve lagoon retention and subsequent spreading on fields, but the sheer volume of production seems to be outstripping these and other technologies. Surface-water runoff finds its way into streams and rivers, ultimately polluting all downstream segments of the watershed. The topic of this paper is spatio-temporal statistical modeling of (log) nitrate concentration in the upper North Bosque watershed, which is a region of concentrated dairy operations. A model is fitted from daily data collected over a period of 15 months at 17 stream monitoring sites throughout the watershed. Optimal predictions of unknown nitrate concentration at all stream locations at any given time are obtained, along with a measure of their variability.

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.

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.

The linked ArcView 2.1 and XGobi environment—GIS, dynamic statistical graphics, and spatial data

This paper reports on research into interactive, dynamic statistical graphics (DSG) applied to spatial data maintained within a geographic information system (GIS). We developed a bidirectional link between ArcView 2.1 , a GIS, and XGobi, a DSG program. Multivariate data, collected at geographic locations, is passed from ArcView to XGobi and can be dynamically analyzed. The relation between the points in XGobi and the spatial locations from where they were collected is maintained so that points in either ArcView or XGobi can be brushed and the corresponding points in the other application are identified immediately. Special features (or flavors) of the link are the handling of multivariate attribute data, spatial cumulative distribution functions, variogram‐cloud plots, spatially lagged scatterplots, and multivariate variogram‐cloud plots.