Abstract
This chapter provides an introduction to geocomputation and geocomputational methods. As such it considers the scope of the term geocomputation, the principal techniques that are applied, and some of the key underlying principles and issues. Chapters elsewhere in this major reference work examine many of these ideas and methods in greater detail. In this connection it is reasonable to ask whether all of modern spatial analysis is inherently geocomputational; the answer is without doubt “no,” but its growing importance in the development of new forms of spatial analysis, in exploration of the behavior and dynamics of complex systems, in the analysis of large datasets, in optimization problems, and in model validation remains indisputable.
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References
Batty M (2000) Geocomputation using cellular automata. Ch 5. In: Openshaw S, Abrahart RJ (eds) Geocomputation. Taylor and Francis, London, pp 95–126
Batty M (2011) A generic framework for computational spatial modeling. Working paper 166. Centre for Advanced Spatial Analysis (CASA), UCL, London. Available from http://www.casa.ucl.ac.uk/publications/workingPaperDetail.asp?ID=166. Accessed 4 Oct 2011
de Smith MJ, Goodchild MF, Longley PA (2009) Geospatial analysis: a comprehensive guide to principles, techniques and software tools, 3rd edn. Troubador Publishing, Leicester. Also available online at http://www.spatialanalysisonline.com
Fischer MM (2006) Spatial analysis and geocomputation: selected essays, vol 1. Springer, Heidelberg
Fischer MM, Leung Y (eds) (2001) GeoComputational modelling. Techniques and applications. Springer, Berlin/Heidelberg/New York
Greene SK, Schmidt MA, Slobierski MG, Wilson ML (2010) Spatio-temporal patterns of viral meningitis in Michigan, 1993–2001. In: Fischer MM, Getis A (eds) Handbook of applied spatial analysis. Software tools, methods and applications. Springer, Berlin/Heidelberg/New York, pp 721–735
Heppenstall AJ, Harland K, Smith DM, Birkin MH (2011) Creating realistic synthetic populations at varying spatial scales: a comparative critique of population synthesis techniques. Geocomputation 2011 conference proceedings. UCL, London, pp 1–8
Huang Q, Yang C, Li W, Wu H, Xie J, Cao Y (2011) Geoinformation computing platforms. Ch. 3. In: Yang R et al (eds) Advanced geoinformation science. CRC Press, Baton Rouge, pp 79–126, op. cit
Kulldorf M (1997) A spatial scan statistic. Commun Stat: Theory Method 26:1481–1496
Openshaw S (1987) A mark 1 geographical analysis machine for the automated analysis of point data sets. Int J Geogr Inf Syst 1:335–358
Openshaw S, Abrahart RJ (eds) (2000) Geocomputation. Taylor and Francis, London. Wikipedia: conway’s game of life. Available from http://en.wikipedia.org/wiki/Conway%27s_Game_of_Life
Wolfram S (1983) Statistical mechanics of cellular automata. Rev Mod Phys 55:601–643
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de Smith, M. (2018). Geospatial Analysis and Geocomputation: Concepts and Modeling Tools. In: Fischer, M., Nijkamp, P. (eds) Handbook of Regional Science. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36203-3_62-1
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DOI: https://doi.org/10.1007/978-3-642-36203-3_62-1
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