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Map Generalization
IntroductionConcepts
conventional cartographygeographic information systems
Developmentsconceptual modelsalgorithmsknowledge representation
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Introduction
Data presentationdisplaycommunication
Data integrationscale and spatial resolutiondata quality
Derivation of spatial databasesspatial modeling
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Concepts
The role of a map is to present a factual statement about geographic reality (Robinson, 1960).
A map is a data model that intervenes between reality and database (Goodchild, 1992).
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Concepts
Map generalization is the simplification of observable spatial variation to allow its representation on a map (Goodchild, 1991).
Map generalization is an information-oriented process intended to universalize the content of a spatial database for what is of interest (Müller, 1991).
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Concepts
Map generalization:
reduces complexityretains spatial and attribute accuracyaccounts for map purpose and scaleprovides more ‘information’ or more
efficient communication
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Feature coalescence
(McMaster and Shea, 1992)
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Feature selection
(Monmonier, 1991)
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Complexity reduction
(McMaster and Shea, 1992)
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Attribute accuracy
(McMaster and Shea, 1992)
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Map purpose
(McMaster and Shea, 1992)
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Developments
1960 to 1975: algorithm development, with emphasis on line simplification.
Late 1970s to 1980s: assessment of algorithm efficiency.
1990s: conceptual models; formalization of cartographic knowledge.
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Developments
Seminal attempts at automation
Julien Perkal: concept of approximate length of order , where is a real number.
Waldo Tobler: computer rules for numerical generalization.
Friedrich Töpfer: amount of information that can be shown per unit area decreases according to geometric progression.
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Conceptual models
Brassel and Weibelstructure recognition
– measures of relative importance
process recognition– definition of generalization process
process modeling– compilation of rules
process execution– generalization of original database
data display
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Conceptual models
McMaster and Sheawhy?
– Complexity reduction, maintenance of spatial and attribute accuracy, map purpose and intended audience, retention of clarity
when?– Geometric conditions, spatial and holistic
measures, transformation control
how?– Spatial and attribute transformation
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Algorithmic approach
Overemphasis on line simplificationLack of a theory to explain which
algorithm is the most appropriate for which object
Obscure view of what is exploitableNecessity to derive methods from
semantic and topology rather than from form and size
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Algorithmic approach
Douglas and Peucker (1973)redundancy in the number of points of digital
lines
Cromley (1992)modification of the Douglas-Peucker algorithmhierarchical structure to store ranked points
Li and Openshaw (1992)concept of the smallest visible objecthybrid vector/raster implementation
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Algorithmic approach
Visual comparisons - perception
Attneave’s cat (1954)
Geometric measureschange in the number of coordinateschange in angularityvector displacementareal displacement
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Knowledge representation
Knowledge acquisition
conventional KE techniques - communication?
analysis of text documentscomparison of map seriesmachine learning and neural networksamplified intelligence
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Knowledge representation
If expert systems are to be based upon a consensual knowledge of experts, the map generalization realm will not be suited to expert systems technology (Rieger and Coulson, 1993).
Cooperative knowledge systems should result from joint research in AI, cognitive science, work psychology, and social sciences (Keller, 1995).
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Research agenda
Objectives of generalization in the digital context
Test scenarios to push the usefulness of existing tools to their limits
Cartographic x model-oriented generalizations
Explicitness of spatial relations for points, lines, and polygons
Research cooperation between mapping agencies and academia
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![Abstract DRAFT - Ahahah · Many advanced digital cartography methods such as graphic generalization [6], la-bel placement [7], legend customization [8, 9], etc. may be introduced](https://img.pdfslide.net/doc/110x75/5f0f799d7e708231d44458bd/abstract-draft-many-advanced-digital-cartography-methods-such-as-graphic-generalization.jpg)
