Multimedia exploratory data analysis for geospatial data mining: The case for augmented seriation

The amount of spatial data collected from satellites, aerial photography, a nd land-based stations continues to grow at astounding rates. In this artic le, the role of exploratory data analysis (EDA) for spatial data mining is reviewed and a case study addressing environmental risk assessments in New York State is presented to illustrate the feasibility and usability of augm enting seriation for spatial data analysis. For this project, seriation, a univariate EDA technique, is augmented with a class of multimedia tools inc luding iconic matrices, choropleth mapping, graphic interactions, and sound to exploit spatial datasets to better understand the relationships among s patial, temporal, and human variables. Additional software enhancements suc h as three-dimensional matrices, multivariate choropleth mapping, and tonal sonification are proposed to further improve these user-based tools for sp atial data analysis.