[AM10-1] Problems of large spatial databases

Difficulties in dealing with large spatial databases, especially those arising from spatial heterogeneity and data quality issues.

Introduction

External resources

• Karimi, H.A. (ed.) (2014) Big Data Techniques and Technologies in Geoinformatics. ISBN 9781138073197 Published April 20, 2017 by CRC Press 312 Pages.

Learning outcomes

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

Self assessment

Outgoing relations

• [AM10-1] Problems of large spatial databases subclassof [AM10] Data mining

Contributors

• Rob Lemmens
  University of Twente, Faculty of Geo-Information Science and Earth Observation (ITC)
  https://research.utwente.nl/en/persons/rob-lemmens