Kening Wang, Charles Stegman, Sean W. Mulvenon, and Yanling Xia University of Arkansas, Fayetteville, AR, Using Kriging and Interactive Graphics in Web-Based Application for Spatial-Temporal Trend Analysis of Ozone and Weather Systems in Central America Abstract This study illustrates a demo system which was designed for supporting web-based interactive visualization and spatial-temporal trend analysis of ozone and weather data in Central America. Longitudinal prediction maps of ozone and surface temperature were generated using Kriging method. Bar charts of air pressure, cloud coverage, and elevation at each measured location were plotted on the maps. Prediction maps, time-series chart, and 3-D graphics are linked and presented through this system. Through building up a relationship between maps and other graphical representations, users are able to effectively explore the data in many different ways and from many different angles. Introduction Environmental data collected by federal government agencies usually are spatial-temporally referenced massive datasets with multivariate measures covering a huge geographic area. Effective visualization and exploration of this kind of datasets create greater challenges. Web-based data visualization can provide users with high user interactivity and it is likely to be very useful for exploring this kind of data. Meanwhile, use of the internet for delivery of data and information also enables a large amount of graphics to be accessible to the public, and encourages users to explore the data in a playful way. Method Kriging method has been reported to be used for ozone prediction (Lefohn et al., 1994). In this study, prediction maps of ozone and surface temperature were generated using Kriging method. Three frequently used models in this study for Kriging are: 1) Spherical model, 2) Exponential model, 3) J-Bessel model. The software ESRI ArcGIS Geostatistical Analyst was used to create prediction maps, because Geostatistical Analyst bridges the gap between Geostatistics and GIS, and it contains a series of easy-to-use tools. The software Nvu, which is a complete web authoring system, was used to develop the web of this project. Results To illustrate the applicability of the proposed approach, we have developed a full-featured demo system at our web site: Users can view 3-D graphic of globe, which shows the geographic area data collected, and project description when they clicking the tab “ MY PROJECT OVERVIEW ”. Users can view the longitudinal prediction maps of ozone and surface temperature. Users can view Time-series chart of ozone. Ozone Patterns The distribution of ozone exhibits strong latitude dependence. Total ozone amounts near the equator are rather low over the course of each year, and increase as we move from tropics to higher latitudes. This phenomenon can be explained by stratospheric circulation, also known as Brewer-Dobson circulation, which transports high ozone from the tropics to the lower stratosphere of the high latitudes. The distribution of ozone also shows strong seasonality dependence. Ozone amounts over the northern region are rather high, with the highest amounts in April, May, and June, then decreasing over summer. The lowest amounts are present in October, rising again over the course of winter. In the winter, we see ozone column amounts are large at high northern latitudes, and low at the tropics. Moving into the summer, we find ozone amounts at high northern latitudes falling off from winter time, and at the same time, tropical ozone increases. Wind transport of ozone is principally responsible for the seasonal evolution of these higher latitude ozone patterns. Users can view graphics of elevation. Users can view graphics of air pressure. Users can view graphics of cloud coverage. Conclusions Buja et al. (1996) proposed a rudimentary taxonomy of interactive view manipulations for high-dimensional data, and they are: focusing individual views, linking multiple views, and arranging many views. This web-based interactive data visualization demo system is one example of focusing, linking, and arranging views; and it is also a valuable complement to the techniques of exploration of large multidimensional datasets which have spatial-temporal components. REFERENCES Buja, A., Cook, D., and Swayne, D. (1996) Interactive High-Dimensional Data Visualization. Journal of Computational and Graphical Statistics, 5, 78–99. Lefohn, A.S.; Simpson, J.; Knudsen, H.P.; Bhumralkar, C.; Logan, J.A. (1994 ) An evaluation of the kriging method to predict 7-h seasonal mean ozone concentrations for estimating crop losses. Journal of Air Pollution Control Association, 37, 595–602. Objectives 1) To provide a graphic summary of important features of the data, and to make the results easily understandable to publics who are not familiar with using geostatistical methods to generate prediction maps. 2) To demonstrate effectiveness of web-based data visualization for exploiting the important relationships between the variables and for revealing the spatial- temporal trends.