The field of visualization is focused on creating images that convey salient information about
underlying data and processes. In the past three decades, the field has seen unprecedented
growth in computational and acquisition technologies,
which has resulted in an increased ability both to sense the physical world with
very detailed precision and to model and simulate complex physical phenomena. Given these
capabilities, visualization plays a crucial enabling role in our ability to comprehend such large
and complex data-data that, in two, three, or more dimensions, conveys insight into such diverse
applications as medical processes, earth and space sciences, complex flow of fluids, and
biological processes, among many other areas.
With this Handbook, we have tried to compile a thorough overview of our young field by
presenting the basic concepts of visualization, providing a snapshot of current visualization
software systems, and examining research topics that are advancing the field.
We have organized the book into parts to reflect a taxonomy we use in our teaching to
explain scientific visualization: basic visualization algorithms, scalar data isosurface methods,
scalar data volume rendering, vector data, tensor data, geometric modeling, virtual environments,
large-scale data, visualization software and frameworks, perceptual issues, and
selected application topics including information visualization. While, as we say, this taxonomy
represents topics covered in a standard visualization course, this Handbook is not
meant to serve as a textbook. Rather, it is meant to reach a broad audience, including
not only the expert in visualization seeking advanced methods to solve a particular problem
but also the novice looking for general background information on visualization topics.