PD-10 - Problems of large spatial databases

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Learning Objectives: 
  • Describe emerging geographical analysis techniques in geocomputation derived from artificial intelligence (e.g., expert systems, artificial neural networks, genetic algorithms, and software agents)
  • Explain how to recognize contaminated data in large datasets
  • Outline the implications of complexity for the application of statistical ideas in geography
  • Explain what is meant by the term “contaminated data,” suggesting how it can arise
  • Describe difficulties in dealing with large spatial databases, especially those arising from spatial heterogeneity