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Alternate abstract:
Considering the shortcomings of inverse distance weighted (IDW) interpolation in practical applications, this study improved the IDW algorithm and put forward a new spatial interpolation method that named as adjusted inverse distance weighted (AIDW). In interpolating process, the AIDW is capable of taking into account the comprehensive influence of distance and position of sample point to interpolation point, by adding a coefficient (K) into the normal IDW formula. The coefficient (K) is used to adjust interpolation weight of the sample point according to its position in sample points. Theoretical analysis and practical application indicates that the AIDW algorithm could diminish or eliminate the IDW interpolation defect of non-uniform distribution of sample points. Consequently the AIDW interpolating is more reasonable, compared with the IDW interpolating. On the other hand, the contour plotting of the AIDW interpolation could effectively avoid the implausible isolated and concentric circles that originated from the defect of the IDW interpolation, with the result that the contour derived from the AIDW interpolated surface is more similar to the professional manual identification.
