Skip to main content

Modelling landscape dynamics with Python

Buy Article:

$55.00 plus tax (Refund Policy)

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.
No Reference information available - sign in for access.
No Citation information available - sign in for access.
No Supplementary Data.
No Article Media
No Metrics

Keywords: Dynamic modelling; Environmental modelling; Error propagation modelling; Monte Carlo simulation; PCRaster; Python

Document Type: Research Article

Affiliations: Department of Physical Geography, Faculty of Geosciences, Utrecht University, 3508 TC Utrecht, The Netherlands

Publication date: 2007-01-01

More about this publication?
  • Access Key
  • Free content
  • Partial Free content
  • New content
  • Open access content
  • Partial Open access content
  • Subscribed content
  • Partial Subscribed content
  • Free trial content
Cookie Policy
X
Cookie Policy
Ingenta Connect website makes use of cookies so as to keep track of data that you have filled in. I am Happy with this Find out more