This volume approaches geography as a cognitive science focusing on the processes used for learning and decision-making. This book argues that geographers need a theoretical understanding of how people process spatial information. How people store and use information they have acquired about environments is considered in a variety of geographic contexts. Cognitive theories and connectionist models are related to geographic problems to explain how spatial information is processed. The nature of cognitive maps, the processes used to encode them, and their systematic distortions are reviewed. A perception theory that explains the temporary tracking of environmental objects is considered as well as a theory that explains how verbal and visual information can be combined to create mental models of geographic environments in long-term memory. Other theories are considered that explain visual search processes used to find symbols or boundaries on maps. The processes used to learn spatial categories and prototypes, to create abstract knowledge in basic-level categories, and to judge the similarity of objects are also addressed. Neural networks are discussed throughout the book and used to model learning and classification processes.
Audience: This book is directed at researchers and students in geography/social geography, psychology and cognitive science interested in spatial cognition.
1: Geography and Cognitive Science. 1.1. Introduction. 1.2. Cognitive Processing. 1.3. Conclusions. 2: A Connectionist Approach to Spatial Cognition. 2.1. Introduction. 2.2. Memory Hardware. 2.3. Map Reading. 2.4. Analyzers. 2.5. Types of Memory. 2.6. Episodic Analyzer. 2.7. Action System. 2.8. Interacting Systems. 2.9. Fuzzy Cognitive Maps. 2.10. Interactive Activation Competition Models. 2.11. Interaction Activation Competition Model as Cognitive Map. 2.12. Conclusions. 3: Cognitive Maps. 3.1. Introduction. 3.2. Encoding Processes. 3.3. Conclusions. 4: Storing Spatial Information in Memory. 4.1. Introduction. 4.2. Object Files. 4.3. Mental Models. 4.4. Conclusions. 5: Spatial Search Processes. 5.1. Introduction. 5.2. Cognitive Theories of Search. 5.3. Geographic Applications. 5.4. Conclusions. 6: Learning Geographic Information. 6.1. Introduction. 6.2. Learning Categories. 6.3. Climate Categories. 6.4. Learning Higher-Order Categories. 6.5. The Organization of Geographic Information. 6.6. Conclusions. 7: Spatial Prototypes. 7.1. Introduction. 7.2. Category Prototypes. 7.3. Using Prototypes. 7.4. When is What Where? 7.5. Conclusions. 8: Similarity. 8.1. Introduction. 8.2. Comparing Maps. 8.3. Theoretical Similarity of Maps. 8.4. Conclusions. 9: Neural Network Applications. 9.1. Introduction. 9.2. Types of Problems. 9.3. The Gravity Model. 9.4. Residential Integration. 9.5. Acquiring Spatial Information. 9.6. Pattern Recognition. 9.7. Conclusions. 10: Conclusions. 10.1. Introduction. 10.2. Summary of Ideas.
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