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Modelling landscape dynamics with Python 

Authors: D. Karssenberg a;  K. de Jong a; J. van der Kwast a
Affiliation:   a Department of Physical Geography, Faculty of Geosciences, Utrecht University, 3508 TC Utrecht, The Netherlands
DOI: 10.1080/13658810601063936
Publication Frequency: 12 issues per year
Published in: journal International Journal of Geographical Information Science, Volume 21, Issue 5 January 2007 , pages 483 - 495
Formats available: HTML (English) : PDF (English)
Previously published as: International journal of geographical information systems (0269-3798, 1362-3087) until 1996
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Abstract

A new tool for construction of models is presented that allows earth scientists without specialist knowledge in programming to convert theories to numerical computer models simulating landscape change through time. This tool, referred to as the PCRaster Python library, consists of: (1) the standard Python programming language, which is a generic, interpreted scripting language, supporting object oriented programming; (2) a large set of spatial and temporal functions on raster maps that are embedded in the Python language as an extension; (3) a framework provided as a Python class to construct and run iterative temporal models and to calculate error propagation with Monte Carlo simulation; and (4) visualization routines to display spatio-temporal data read and written by this framework. Python is a high-level programming language, and users of the tool do not have to be specialist computer programmers. Users of the PCRaster Python library can take advantage of several other Python libraries, such as extensions for matrix algebra and for modelling in three spatial dimensions.
Keywords: Dynamic modelling; Monte Carlo simulation; Error propagation modelling; Python; PCRaster; Environmental modelling
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