Geographical Models with Mathematica provides a fairly comprehensive overview of the types of models necessary for the development of new geographical knowledge, including stochastic models, models for data analysis, for geostatistics, for networks, for dynamic systems, for cellular automata and for multi-agent systems, all discussed in their theoretical context.
The author then provides over 65 programs, written in the Mathematica language, that formalize these models. Case studies are provided to help the reader apply these programs to their own studies.
- Provides theoretical, stochastic and dynamic system models
- Covers data science, both in a spatial and spatio-temporal analysis
- Presents a microstructural understanding of the mechanical behavior of granular materials
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Part 1: Modeling the Relationships between Societies and Nature Introduction 1. The Theoretical Context of Classical Geography 2. Statistical and Probability Models for Given Relationships Between Societies and the Natural Environment 3. Models of Ordinary Dynamic Systems
Part 2: Modeling Geographic Locations Introduction 4. Theories of Geographical Locations 5. Theoretical Geolocation Models
Part 3: Spatial Structures and Territorial Dynamics Introduction 6. Theories Used to Understand Territorial Structures and Dynamics 7. Models of Basic Structures: Points and Fields 8. Models of Basic Structures: Networks 9. Geographical Space as a Mixture of Basic Spatial Structures 10. Morphogenetic Macro- and Micro-models
Andre Dauphine is Honorary Dean of the University of Nice Sophia-Antipolis in France, founder member of the Dupont Group and a recognized expert in theoretical and quantitative geography. He is the author of books on the theories of complexity, fractal geography, risks and disasters.