Computational science is a discipline focused on the design, implementation and use of mathematical models or simulations through the use of computers to analyse scientific problems, systems or processes. Computational science heavily relies on computational technologies such as high performance computing, artificial intelligence, computational intelligence, grid infrastructure and parallel computing. Geocomputation is closely related to computational science and, therefore, geocomputational methods are often derived from machine learning, clustering, simulation, parallel computing and high performance computing. Contrary to the methods and tools applied for spatial analysis described under the Analytical Methods Knowledge Area, geocomputation and spatial data science may involve the use of spatial methods available in standard GIS packages, but quite often require self-development, or at least customisation, involving computational technologies and coding to solve target problems. The aim of this topic is to provide an introduction to computational science with particular emphasis on its usage and relation to geocomputation. In this sense, the way computational technologies are used in computational science can be connected to the methodological and coding practices of geocomputation and spatial data science.
this concept has been renamed from "Theory of Geocomputational methods"
Define and discuss opportunities and limitations of computational science
Examine how computational technology relates to geocomputation
Completed (GI-N2K)