The natures of maps: cartographic constructions of the natural world (original) (raw)

Toward Self-Generalizing objects and On-the-Fly map generalization

… : The International Journal for …, 2008

Map generalization is a complex task that sometimes requires human intervention. In order to support such a process on the fly, we propose a generalization approach based on self-generalizing objects (SGOs) that encapsulate geometric patterns (forms common to several cartographic features), generalization algorithms, and spatial integrity constraints. During a database enrichment process, an SGO is created and associated with a cartographic feature or a group of features. Each SGO created is then transformed into a software agent (SGO agent) in a multi-agent on-the-fly mapgeneralization system. SGO agents are equipped with behaviours that enable them to coordinate the generalization process. This article presents the concept of the SGO and two prototypes developed to support this approach: a prototype for the creation of SGOs and another for the on-the-fly map generalization (which uses the created SGOs).

The Application of Agents in Automated Map Generalisation

2000

This paper reports on current research utilising agent based methodologies in order to provide solutions in autonomous map generalisation. The research is in pursuit of systems able to support the derivation of multi scaled products from a single detailed database with minimal human intervention in the map compilation process. Such research has important implications for automated conflation (multiple database integration),and

Automated map generalisation using communicating agents

2003

This research is concerned with automating the generalisation of topographic databases, in order to produce topographic maps. We use an agent-oriented approach: the geographic features (roads, rivers, buildings etc.) are modelled as autonomous agents, as previously undertaken within the European AGENT project (1). To handle rural areas, our approach consists of letting these agents interact so that each of them either finds a new location and geometric representation or eliminates itself, so that the whole fits within the generalisation specifications. For this, our agents are provided with capacities to perceive their spatial environment, as well as an ability to communicate with surrounding agents. This approach has been implemented and tested on real geographical data. In this paper we describe the system. Some encouraging results are presented and discussed.

Collaborative Generalisation: Formalisation of Generalisation Knowledge to Orchestrate Different Cartographic Generalisation Processes

Lecture Notes in Computer Science, 2010

Cartographic generalisation seeks to summarise geographical information from a geographic database to produce a less detailed and readable map. This paper deals with the problem of making different automatic generalisation processes collaborate to generalise a complete map. A model to orchestrate the generalisation of different areas (cities, countryside, mountains) by different adapted processes is proposed. It is based on the formalisation of cartographic knowledge and specifications into constraints and rules sets while processes are described to formalise their capabilities. The formalised knowledge relies on generalisation domain ontology. For each available generalisation process, the formalised knowledge is then translated into process parameters by an adapted translator component. The translators allow interoperable triggers and allow the choice of the proper process to apply on each part of the space. Applications with real processes illustrate the usability of the proposed model.

Database-stored Representations and Overrides, Supporting Automated Cartography with Human Creativity

Geographic information systems centered on relational databases are a powerful and proven way to collect, store, and analyze geographic data. Such systems are also used to produce cartographic products including maps and mapping datasets. However, existing mapping systems built on GIS databases fail to fully leverage relational database technology, mainly because most systems store geographic information—geometry and attributes—in the relational database, but store map definition and symbolization information in separate files. Also, map symbolization is accomplished by applying rules that assign symbology to sets of categorized features, a system that is seen by many cartographers as being too restrictive in not allowing one to interactively change individual cartographic graphic representations. This paper proposes a GIS-based cartographic production system where cartographic information is stored with GIS data in the relational database. A system whereby dynamic cartographic symb...

Cartographic generalization as a combination of representing and abstracting knowledge

Proceedings of the seventh ACM international symposium on Advances in geographic information systems - GIS '99, 1999

This article shows that cartographic generalization is best viewed as representing (formulating, renaming knowledge) and abstracting (simplifying a given representation). The general process of creating map is described so as to show how it fits into an abstraction framework developed in artificial intelligence to emphasize the difference between abstraction and representation. The utility of the framework lies in its efficiency to automate knowledge acquisition for the cartographic generalization as a combined acquisition of knowledge for abstraction and knowledge for changing a representation.