Comparison Of Interpolation Techniques Research Articles

Comparison of interpolation techniques used in Bioclimatic comfort maps and approach developed through Raster calculation model

Comparison of interpolation techniques used in Bioclimatic comfort maps and approach developed through Raster calculation model

Geostatistical analysis of arsenic contamination in soil and comparison of interpolation techniques in Nadia district of Bengal, India

The contamination of soil and water with arsenic directly or indirectly affects millions of people, particularly in Southeast Asia. Efficiently managing contaminated sites cost-effectively requires an understanding of the spatial distribution of contamination in soil. In this study, different interpolation methods, including Ordinary Kriging (OK), Inverse Distance Weighted (IDW), Radial Basis Function (RBF), and Empirical Bayesian Kriging (EBK), were evaluated in the Bengal region to determine their effectiveness in predicting the Olsen extractable As content in the soil. The study found that the mean Olsen extractable content in soil was 1.45 mg kg-1 , with a range of 0.48 to 3.57 mg kg-1 . Geostatistical analysis showed that the northern side of Nadia had relatively high contamination, while the southern side had relatively lower contamination. The Root Mean Square Error (RMSE) values of the different interpolation methods ranged from 0.52 to 0.54, with corresponding mean cross-validation (CV) values ranging from -0.005 to 0.008. The predicted minimum and maximum values of as-in soil were in close agreement with the measured values for IDW interpolation, followed by OK, RBF, and EBK. The study found that IDW consistently provided the most precise predictions of pollution in the soil throughout space. These findings have significant implications for managing contamination in the Nadia West Bengal and other regions facing similar challenges.

Subsurface mapping: selection of best interpolation method for borehole data analysis

Selection of the best interpolation method as well as the appropriate software parameters that give the closest approximation to known geology is usually a difficult task. This is because geologic factors such as lithologic and structural feature occurrences are not easily predictable, especially where outcrop occurrences are fortuitous. Borehole data provides an alternative to sparse outcrops especially in areas where the borehole occurrence is well-distributed. However, most boreholes were drilled for exploration purposes and may not be well-distributed over all the study areas. Getting information in-between boreholes becomes a big challenge, especially in areas where we have very large volume of borehole data that are randomly distributed. The use of interpolation technique to estimate in-between borehole points becomes imperative. Comparison of interpolation techniques was carried out with borehole log data so as to determine the best interpolation method output that is closest to known geology. The test area is located in the southwestern part of the Western Bushveld Complex and the northeastern part of the Eastern Bushveld Complex in South-Africa. Eight interpolation tools available in Rockworks® 15 were evaluated and utilized in contouring the major stratigraphic peaks within the area. The best results were achieved with Kriging and trend surface analysis interpolation methods. The resultant maps were interpreted and compared with geology and structures inferred from existing geological and geophysical records and a good correlation is present.