Map Generalization:

Background

When features are generalised their level of detail is reduced but their overall shape and position is retained. The generalisation of digital spatial data is done for various reasons including:

For example, a small scale map of a coastline will not show every cove that might appear on a large scale map. Smaller scale maps may also omit features completely. It is important to note that data can always be generalised to a smaller scale but cannot be created for larger scales.

Generalisation of vector data can be applied to points, lines and polygons and there are a number of different algorithms that are used in GIS to handle these processes. Two commonly used generalisation operators that can be applied to line data are line simplification and line smoothing.

Line Simplification

GISsimplification.png

Line simplification algorithms remove from the line redundant or unnecessary coordinate pairs based on some geometric criterion, such as distance between points or displacement from a centreline. Line simplification can result in:


This figure shows a line before and after it has been simplified, with arrows representing the points eliminated during the process.

Line Smoothing

GISsmoothing.png
Line smoothing routines relocate or shift coordinate pairs. Unlike simplification, which endeavours to reduce detail, smoothing techniques shift the position of points making up a line, in order to remove small irregularities and capture only the most significant trends of the line. This result in the improved appearance of the lines. 

This figure shows a line before and after it has been smoothed.