Modelling knowledge for automated generalisation of categorical maps—a constraint based approach

Abstract

This research is concerned with the automatic derivation of multi scaled categorical maps from a single detailed database. The representation of categorical maps at increasing scales requires us to aggregate detailed categorical data, such as is found in capability maps or soil maps (Burrough, 1991) in order to produce a series of simplified, visually effective maps. As a prerequisite to implementation within an object oriented GIS, a model is required that enables us to represent these transitions in a systematic meaningful way. Such a model must take into account the special characteristics unique to categorical maps. A categorical map is a space exhaustive tessellation of space. The discrete boundaries we see on the map are rarely found in the landscape. The reality is that they represent inherently fuzzy phenomena (Burrough and Frank, 1996), and their form is very dependent on the classification used. Such characteristics present challenging environments for automated generalisation solutions, with strong spatial and semantic interdependencies existing between the polygons that define the various spatial extents. The research is pertinent due to the increasing demand for and use of Internet based products, generalised in both scale and theme. Given the lack of requisite cartographic skills, there is a need to capture the necessary cartographic knowledge in order to automate this process.

Cite this work

No public copy is stored for this record, so only the metadata is cited.

Stored only when both papers are in the corpus — 7 citations exist upstream.

Papers that cite the same references — the relational fallback while embeddings are still backfilling.