Forecasting Hotspots-A Predictive Analytics Approach.

Current visual analytics systems provide users with the means to explore trends in their data. Linked views and interactive displays provide insight into correlations among people, events, and places in space and time. Analysts search for events of interest through statistical tools linked to visual displays, drill down into the data, and form hypotheses based upon the available information. However, current systems stop short of predicting events. In spatiotemporal data, analysts are searching for regions of space and time with unusually high incidences of events (hotspots). In the cases where hotspots are found, analysts would like to predict how these regions may grow in order to plan resource allocation and preventative measures. Furthermore, analysts would also like to predict where future hotspots may occur. To facilitate such forecasting, we have created a predictive visual analytics toolkit that provides analysts with linked spatiotemporal and statistical analytic views. Our system models spatiotemporal events through the combination of kernel density estimation for event distribution and seasonal trend decomposition by loess smoothing for temporal predictions. We provide analysts with estimates of error in our modeling, along with spatial and temporal alerts to indicate the occurrence of statistically significant hotspots. Spatial data are distributed based on a modeling of previous event locations, thereby maintaining a temporal coherence with past events. Such tools allow analysts to perform real-time hypothesis testing, plan intervention strategies, and allocate resources to correspond to perceived threats.

Graphical perception and graphical methods for analyzing scientific data.

Graphical perception is the visual decoding of the quantitative and qualitative information encoded on graphs. Recent investigations have uncovered basic principles of human graphical perception that have important implications for the display of data. The computer graphics revolution has stimulated the invention of many graphical methods for analyzing and presenting scientific data, such as box plots, two-tiered error bars, scatterplot smoothing, dot charts, and graphing on a log base 2 scale.

Variables on scatterplots look more highly correlated when the scales are increased.

Judged association between two variables represented on scatterplots increased when the scales on the horizontal and vertical axes were simultaneously increased so that the size of the point cloud within the frame of the plot decreased. Judged association was very different from the correlation coefficient, r, which is the most widely used measure of association.

Photochemical air pollution in the northeast United States.

Statistical analyses of meteorological and contaminant data and chemical kinetic modeling demonstrate that (i) the concentrations of ozone in the New Jersey-New York City metropolitan area are regional in character; (ii) ozone concentrations in Connecticut are increased by approximately 20 percent as a consequence of primary emissions in the New Jersey-New York City metropolitan region and subsequent transport; and (iii) the concentrations of a variety of products of smog chemistry in the New Jersey area are markedly increased by an increase in NO emissions, but are minimally affected by a change in hydrocarbon emissions.

The use of numerical and graphical statistical methods in the analysis of data on learning to see complex random-dot stereograms.

Several numerical and graphical statistical methods are illustrated in an analysis of data from an experiment that investigated a hypothesis of Julesz that giving a person a priori information about the structure of a complex random-dot stereogram reduces the time needed to perceive it when it is viewed. The data are divided into two groups, one consisting of those observers who received no cue or verbal cues (NV) and the other consisting of those who received verbal-visual cues (VV). A quantile-quantile plot shows that the NV times (mean = 7.6) are longer than the VV times (mean =5.6). By using probability plots, it is shown that the perception times have an exponential probability distribution. A hypothesis test based upon this distribution is used to show that the difference between the NV and VV times has significance slightly below 0.05.

Photochemical air pollution: transport from the New York City area into Connecticut and Massachusetts.

Photochemical air pollution resulting from primary emissions in the New York City metropolitan area is transported by prevailing winds on a 300-kilometer northeast trajectory through Connecticut and as far as northeastern Massachusetts. As a result, southwestern Connecticut has the highest ozone concentrations in the region and there is a substantial increase in ozone concentrations in Massachusetts. The ozone concentrations of air entering the New York City metropolitan area are often already above the federal standard of 0.08 part per million, but the concentration distribution is well below concentration distributions at downwind sites in Connecticut.

Sunday and workday variations in photochemical air pollutants in new jersey and new york.

Concentration distributions of air contaminants and meteorological variables in New Jersey and New York for workdays (Mondays through Fridays, omitting holidays) and Sundays are compared by means of quantile-quantile plots. The ozone distributions are slightly higher on Sundays, and the primary pollutant distributions are lower. These results raise serious questions about the validity of current concepts underlying ozone reduction in urban atmospheres.

Ozone concentrations in new jersey and new york: statistical association with related variables.

The concentrations of ozone at nine measurements sites in New Jersey and New York during the period 1 May through 30 September 1973 have been examined. Daily fluctuations in the ozone concentrations at any two sites are highly correlated. The concentrations are lower with low levels of solar radiation and also with high wind speed. The average ozone concentration shows only minor differences between weekdays and weekends, despite markedly different traffic patterns.