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COMPARISON OF SPATIAL INTERPOLATION METHODS

Cheng Xin

Open publisher page 56 citations

Abstract

Spatial interpolation can be classified in accordance with their basic hypotheses and mathematical natures as: geometric method, statistical method, geostatistical method, stochastic simulation method, physical model simulation method and combined method. The application areas, special algorithm, advantages and disadvantages of each interpolation method are introduced and compared in the paper. The comparison shows that there is no absolutely optimal spatial interpolation method; there is only relatively optimal interpolation method in special situation. Hence, the best spatial interpolation method should be selected in accordance with the qualitative analysis of the data, exploratory spatial data analysis and repeated experiments. In addition, the result of spatial interpolation should be strictly examined for its validity. Development of general software for spatial interpolation and strengthening the basic theory research are key issues in the future.

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What this paper is about

Spatial interpolation can be classified in accordance with their basic hypotheses and mathematical natures as: geometric method, statistical method, geostatistical method, stochastic simulation method, physical model simulation method and combined method. The application areas, special algorithm, advantages and disadvantages of each interpolation method are introduced and compared in the paper. The comparison shows that there is no absolutely optimal spatial interpolation method; there is only relatively optimal interpolation method in special situation. Hence, the best spatial interpolation method should be selected in accordance with the qualitative analysis of the data, exploratory spatial data analysis and repeated experiments. In addition, the result of spatial interpolation should be strictly examined for its validity. Development of general software for spatial interpolation and strengthening the basic theory research are key issues in the future.

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OpenAlex reports 56 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Spatial interpolation can be classified in accordance with their basic hypotheses and mathematical natures as: geometric method, statistical method, geostatistical method, stochastic simulation method, physical model simulation method and combined method. The application areas, special algorithm, advantages and disadvantages of each interpolation method are introduced and compared in the paper. The comparison shows that there is no absolutely optimal spatial interpolation method; there is only relatively optimal interpolation method in special situation. Hence, the best spatial interpolation method should be selected in accordance with the qualitative analysis of the data, exploratory spatial data analysis and repeated experiments. In addition, the result of spatial interpolation should be strictly examined for its validity. Development of general software for spatial interpolation and strengthening the basic theory research are key issues in the future.

Key concepts: Interpolation (computer graphics), Multivariate interpolation, Nearest-neighbor interpolation, Computer science, Trilinear interpolation, Inverse quadratic interpolation, Spatial analysis, Stairstep interpolation

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