GEOSTATISTIC COMPARISON OF CRIGING AND CO-CRIGING METHODS USING CRIGING POINT ESTIMATION

  • Arief Pambudi Nugraha Universitas Pembangunan Nasional "Veteran" Yogyakarta
Keywords: geostatistics, variogram model, kriging, point estimate, co-kriging

Abstract

This study aims to determine a variogram model with kriging and co-kriging with point kriging and point co-kriging estimation based on linear, exponential, spherical, gaussian variogram models and in isotropic and anisotropic orientations. The research method includes assay analysis of 132 data with the primary variable (Ur) having 24 data and the secondary variable (C) having 126 data. Data processing was done by looking for a model for each method in isotropic and anisotropic orientations. The determination of the model used cross validation by looking at the regression parameters R2, SE, and SE prediction. The results obtained are the kriging method, the best model is the spherical and the co-kriging method is the exponential model. From the comparison of the two methods, the isotropic orientation is better than anisotropic in terms of error and the results of the co-kriging method have a better estimate than kriging.

References

1. B. I. Harman, H. Koseoglu, and C. O. Yigit, “Performance evaluation of IDW, Kriging and multiquadric interpolation methods in producing noise mapping”: A case study at the city of Isparta, Turkey. Applied Acoustics, 112, pp. 147-157, 2016.
2. Guskarnali, “Metode Point Kriging Untuk Estimasi Sumberdaya Bijih Besi (Fe) Menggunakan Data Assay (3D).” Promine Journal, 4 (2), pp. 13-20, 2016.
3. W. S. Bargawa, A. Rauf, and N. A. Amri, “Gold resource modeling using pod indicator kriging.” Progress in Applied Mathematics in Science and Engineering Proceedings. AIP Conf. Proc. 1705, pp. 020025-1-120025-8, 2016.
4. Zulkarnain and W. S. Bargawa, “Classification of coal resources using drill hole spacing analysis (DHSA),” Journal of Geological Resource and Engineering, 6, pp. 151-159, 2018.
5. K. Kang, C. Qin, B. Lee, and I. Lee, “Modified screening-based kriging method with cross-validation and application to engineering design.” Applied Mathematical Modelling, 70, pp. 626-642, 2019.
6. V. Senapathi, and C. R. Paramasivam, “An introduction to various spatial analysis techniques,” in GIS and Geostatistical Techniques for Groundwater Science, 2019, pp. 23-30.
7. W. S. Bargawa, R. F. Tobing, “Iron Ore Resource Modeling and Estimation Using Geostatistics”, AIP Conf. Proc. 2019, Corrected proof, In Press.
8. W. S. Bargawa, “Mineral resources estimation using weighted jackknife kriging.” Advances of Science and Technology for Society. AIP Conf. Proc. 1755, pp. 120001-120006, 2016.
9. W. S. Bargawa, “Weighted jackknife ordinary kriging - problem solution of the precision in mineral resources estimation,” IOP Conf. Series: Earth and Environmental Science 212 (012059), pp.1-9, 2018.
10. W. S. Bargawa, A. Rauf, and N. A. Amri, “Gold resource modeling using pod indicator kriging.” Progress in Applied Mathematics in Science and Engineering Proceedings. AIP Conf. Proc. 1705, pp. 020025-1-120025-8, 2016.
Published
2020-10-27
How to Cite
Arief Pambudi Nugraha (2020) “GEOSTATISTIC COMPARISON OF CRIGING AND CO-CRIGING METHODS USING CRIGING POINT ESTIMATION”, ReTII, pp. 177-181. Available at: //journal.itny.ac.id/index.php/ReTII/article/view/2013 (Accessed: 30July2021).