GeoComputational methods for surface and field data interpolation
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GeoComputation is a relatively recent and emergent discipline containing numerous methods and techniques for fields such as electrical engineering, computer science, geography, biology. This thesis set out to describe the development of the research domain for GeoComputation and learning area so, to compare and evaluate the methods conventionally used for problem definition and investigation by those working in the discipline. In recent years, this field has extended beyond geospatial data processing, analysis and depiction to incorporate refined methods of mathematical modelling (particularly for spatio-temporal data point estimation of discrete and continuous event/instance values) and the anticipation (and prediction) of events in Nature. In some cases that are referenced in this thesis, successful solutions to scientific problems have been generated by combining techniques from geographical information systems with those from emerging computer science research areas such as neuro-computing, data mining (heuristic searching for example) and cellular automata. The methods used for data analysis are examined as they are applied for two case studies and conclusions regarding their worth are outlined.