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Line structure in graphic and geographic space / Barbara P. Buttenfield (1984)

Public Titre : Line structure in graphic and geographic space Type de document : Thèse/HDR Auteurs : Barbara P. Buttenfield, Auteur Editeur : Seattle : University of Washington Année de publication : 1984 Importance : 303 p. Format : 21 x 30 cm Note générale : Bibliographie A dissertation submitted in partial fulfillment of the requirements for the degree of doctor of philosophy Langues : Anglais (eng) Descripteur : [Termes IGN] algorithme de généralisation [Termes IGN] base de connaissances [Termes IGN] ligne (géométrie) [Termes IGN] objet géographique linéaire [Vedettes matières IGN] Généralisation Index. décimale : THESE Thèses et HDR Résumé : (auteur) The research reported in this dissertation has been based on the idea that a cartographic line is a probabilistic representation of the geographic feature which it symbolizes. Numeric parameters have been measured for two orders of structural relationships, and these parameters have been shown to provide significant distinctions between categories of cartographic line structure. The categories which have been developed are not intended as an exhaustive typology of line structure, but rather to demonstrate that meaningful categories of graphic structure can be defined numerically, and statistically verified. Categories for both orders of structure have been summarized graphically, as structure signatures, and digitally, by storing parameters for each category as a computer look-up table. Structure signatures can be applied to cartographic line generalization in several ways which utilize the digital look-up tables. One application involves generating lines of predictable graphic structure, by stochastic modeling techniques. The other application does not serve to generate line structures, but to identify them, to provide a means by which threshold criteria may be automatically set and modified during computer generalization. Line identification proceeds by matching measured parameters against parameters stored in the look—up tables. A possible problem arises when a line is identified which does not match any of the existing structure categories_ An algorithm is presented which has the flexibility to incorporate new structures into an existing knowledge base, in effect, to learn new structures, and to become more proficient in line identification over time. Intelligent algorithms have been developed for pattern recognition by other authors, but the contribution of this research is to provide an intelligent algorithm for a specifically cartographic task, the automated modification of tolerance criteria during line generalization. Note de contenu : Introduction 1. Accuracy in Generalization. 2. Treatment of the Cartographic Line 2.1. The Line as a Set of Equiprobable Points 2.2. The Line as a Linear Feature 2.3. Digression: Peculiarities of Geographic Length 2.4. The Line as an Areal Feature of Finite Width 2.5. The Line as a Spectral Feature 2.6. Digression: Lines of Fractional Dimension 2.7. The Line as a Perceptual Phenomenon 2.8. Summary 3. Components of Line Information 3.1. Recognition and Representation 3.2. Character and Structure in a Probabilistic Context 3.3. A Parametric Definition of Line Structure 4. A Procedural Definition of Line Structure 4.1. The Sample Cartographic Lines 4.2. Three Alternatives for Structural Description 4.3. Justification for the Procedural Description 4.4. Choosing the Measurement Parameters 4.5. Building the Strucutre Signatures 4.6. Signatures for Low Order Structure 4.7. Summary 5. Low and High order structure 5.1. Relationships between Parameters of struture 5.2. Distinctions between Categories and of Lines 5.3. Aspects of MEasuring High Order Structure 5.4. Parameters of High Order Structure 5.5. Classifying Categories of Features 5.6. Summary 6. Working with Cartographic Structure 6.1. Stochastic Modelling of Cartographic Lines 6.2. Computer Identification of Cartographic Lines 6.3. Summary Conclusion Numéro de notice : 19701 Affiliation des auteurs : non IGN Thématique : GEOMATIQUE/INFORMATIQUE Nature : Thèse étrangère Note de thèse : PhD dissertation : Géomatique : Washington : 1984 Permalink : https://documentation.ensg.eu/index.php?lvl=notice_display&id=82606