Authors / CoAuthors
Li, J. | Heap, A.
Abstract
Spatial interpolation methods are often data-specific or even variable-specific. Many factors affect the performance of the methods and there are no consistent findings about their effects. Hence it is difficult to select an appropriate method for a given dataset. This review provides guidelines and suggestions regarding application of spatial interpolation methods to environmental data by comparing the features of the commonly applied methods which fall into three categories, namely: non-geostatistical interpolation methods, geostatistical interpolation methods and combined methods. Factors affecting the performance, including sampling design, sample spatial distribution, data quality, correlation between primary and secondary variables, and interaction among factors, are discussed. A total of 26 methods are then classified based on their features to provide an overview of the relationships among them. These features are quantified and then clustered to show similarities among these 26 methods. A decision tree for selecting an appropriate method from these 26 methods is developed based on data availability, data nature, the expected estimation and the features of each method. A list of software packages for spatial interpolation is provided. Finally, some recommendations are made for applying the methods to marine environmental data.
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nonGeographicDataset
eCat Id
68725
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Keywords
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- External PublicationScientific Journal Paper
- ( Theme )
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- marine
- Australian and New Zealand Standard Research Classification (ANZSRC)
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- Earth Sciences
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- Published_Internal
Publication Date
2009-03-17T00:00:00
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