Generalization, Cartographic

All maps are abstractions of reality, as a map must selectively illustrate some of the features on the surface of the earth. Cartographic generalization is the process of reducing the information content of maps due to scale change, map purpose, intended audience, and/or technical constraints. For instance, when reducing a 1:50,000 topographic map (large scale) to 1:250,000 (small scale), some of the geographical features must be either eliminated or modified, since the amount of map space is significantly reduced. Many decisions must be made in generalization, including which feature classes or features to select, how to modify these features and reduce their complexity, and how to represent the generalized feature. While there are many different generalization operations, a few key ones, classification, simplification, and smoothing, are discussed briefly in this entry.

[Page 162]Cartographers have written on the topic of cartographic generalization since the early part of the 20th century. Max Eckert, the seminal German cartographer and author of Die Kartenwissenschaft, wrote about subjectivity in mapmaking. Over the past 100 years, cartographers have struggled with the intrinsic subjectivity of the generalization process as they have attempted to understand and define cartographic generalization and to break it down into a set of definable processes. The sequencing of these operations is also critical; significantly different results can result from their ordering. This is also an issue of increasing concern with automation, as computers require exact instructions on which algorithms to use and their order of processing.

The generalization process supports several goals, including digital data storage reduction, scale manipulation, and statistical classification and symbolization. Digital generalization can be defined as the process of deriving from a data source a symbolically or digitally encoded cartographic data set through the application of spatial and attribute transformations. The objectives of digital generalization are (a) the reduction in scope and amount, type, and cartographic portrayal of mapped or encoded data consistent with the chosen map purpose and intended audience and (b) the maintenance of graphical clarity at the target scale. The theoretical “problem” of generalization in the digital domain is somewhat straightforward: the identification of areas to be generalized and the application of appropriate operations.

Generalization has three significant aspects: the theoretical objectives, or why to generalize; the cartometric evaluation, or when to generalize; and the specific spatial and attribute transformations, or how to generalize.