Cellular automata (CA) are simple models that can simulate complex processes in both space and time. A CA consists of six defining components: a framework, cells, a neighborhood, rules, initial conditions, and an update sequence. CA models are simple, nominally deterministic yet capable of showing phase changes and emergence, map easily onto the data structures used in geographic information systems, and are easy to implement and understand. This has contributed to their popularity for applications such as measuring land use changes and monitoring disease spread, among many others.

Classification and clustering are often confused with each other, or used interchangeably. Clustering and classification are distinguished by whether the number and type of classes are known beforehand (classification), or if they are learned from the data (clustering). The overarching goal of classification and clustering is to place observations into groups that share similar characteristics while maximizing the separation of the groups that are dissimilar to each other. Clusters are found in environmental and social applications, and classification is a common way of organizing information. Both are used in many areas of GIS including spatial cluster detection, remote sensing classification, cartography, and spatial analysis. Cartographic classification methods present a simplified way to examine some classification and clustering methods, and these will be explored in more depth with example applications.

Color is the result of the visual perception of an energy source. It is described by its physical characteristics, mainly as a tridimensional variable modeled into a color space. Online tools exist to facilitate the use of color schemes to design a color palette, for artists, web designers, statisticians, etc. Colors in maps and visualizations must be combined to promote the visual hierarchy and harmony, balancing legibility, perceptual processing, and aesthetics. Color is a powerful visual variable and requires understanding the perception of color relationships. Existing color schemes are very useful to select a suitable color palette. As color is not experienced similarly across all map readers, issues about real-world connotations, conventions, specific color contrasts, and adaptation to color visual deficiencies and devices, are also to be taken into account when designing a color palette. This entry describes the main guidelines regarding color theory and related design practices as applied to map or geovisualization design.