Comparing ordinary kriging and inverse distance weighting for soil as pollution in Beijing

2018 ◽  
Vol 25 (16) ◽  
pp. 15597-15608 ◽  
Author(s):  
Pengwei Qiao ◽  
Mei Lei ◽  
Sucai Yang ◽  
Jun Yang ◽  
Guanghui Guo ◽  
...  
Keyword(s):  
Ordinary Kriging ◽  
Inverse Distance Weighting ◽  
Distance Weighting ◽  
Inverse Distance

scholarly journals Assessment of Ordinary Kriging and Inverse Distance Weighting Methods for Modeling Chromium and Cadmium Soil Pollution in E-Waste Sites in Douala, Cameroon

2020 ◽  
Vol 10 (26) ◽  
pp. 200605
Author(s):  
Romaric Emmanuel Ouabo ◽  
Abimbola Y. Sangodoyin ◽  
Mary B. Ogundiran
Keyword(s):  
Urban Areas ◽  
Ordinary Kriging ◽  
Cross Validation ◽  
Interpolation Method ◽  
Waste Recycling ◽  
Inverse Distance Weighting ◽  
P Value ◽  
Interpolation Methods ◽  
Distance Weighting ◽  
Inverse Distance

Background. Several studies have demonstrated that chromium (Cr) and cadmium (Cd) have adverse impacts on the environment and human health. These elements are present in electronic waste (e-waste) recycling sites. Several interpolation methods have been used to evaluate geographical impacts on humans and the environment. Objectives. The aim of the present paper is to compare the accuracy of inverse distance weighting (IDW) and ordinary kriging (OK) in topsoil analysis of e-waste recycling sites in Douala, Cameroon. Methods. Selecting the proper spatial interpolation method is crucial for carrying out surface analysis. Ordinary kriging and IDW are interpolation methods used for spatial analysis and surface mapping. Two sets of samples were used and compared. The performances of interpolation methods were evaluated and compared using cross-validation. Results. The results showed that the OK method performed better than IDW prediction for the spatial distribution of Cr, but the two interpolation methods had the same result for Cd (in the first set of samples). Results from Kolmogorov-Smirnov and Shapiro-Wilk tests showed that the data were normally distributed in the study area. The p value (0.302 and 0.773) was greater than 0.05 for Cr and for Cd (0.267 and 0.712). In the second set of samples, the OK method results (for Cd and Cr) were greatly diminished and the concentrations dropped, looking more like an average on the maps. However, the IDW interpolation gave a better representation of the concentration of Cd and Cr on the maps of the study area. For the second set of samples, OK and IDW for Cd and Cr had more similar results, especially in terms of root mean square error (RMSE). Conclusions. Many parameters were better identified from the RMSE statistic obtained from cross-validation after exhaustive testing. Inverse distance weighting appeared more adequate in limited urban areas. Competing Interests. The authors declare no competing financial interests

scholarly journals COMPARISON THE PERFORMANCE OF ORDINARY KRIGING AND INVERSE DISTANCE WEIGHTING METHODS FOR MAPPING NICKEL LATERITE PROPERTIES

KURVATEK ◽  
2019 ◽  
Vol 4 (1) ◽  
pp. 57-67
Author(s):  
Hendro Purnomo
Keyword(s):  
Root Mean Square Error ◽  
Mean Square Error ◽  
Ordinary Kriging ◽  
Cross Validation ◽  
Inverse Distance Weighting ◽  
Mean Square ◽  
Nickel Laterite ◽  
Distance Weighting ◽  
Inverse Distance ◽  
Weighting Methods

Pemilihan metode interpolasi yang sesuai untuk memprediksi kadar bijih pada lokasi yang tidak tersampel merupakan hal yang penting untuk pemetaan sebaran anomaly kadar dan estimasi sumberdaya. Tujuan penelitian ini dilakukan untuk mengevaluasi hasil estimasi metode ordinary kriging (OK) dan inverse distance weighting (IDW) dalam pemetaan distribusi dan potensi sumberdaya nikel (Ni) dan cobalt (Co) pada zona limonit dan saprolit. Dalam penelitian ini digunakan aplikasi perangkat lunak ArcGis 10.2 dengan Geostatistical Analyst Extention untuk menganalisis data. Untuk pemilihan model variogram dan interpolasi yang terbaik digunakan nilai parameter root mean square error (RMSE) yang diperoleh dari prosedur cross validation. Fitting variogram eksperimental dilakukan dengan model spherical, exponential dan gaussian, sedangkan pemilihan model variogram terbaik dilakukan berdasarkan nilai RMSE terkecil. Pada zona limonit, metode IDW dengan power 2 mempunyai performa terbaik untuk kadar Ni dan Co, sedangkan prosedur OK menghasilkan performa terbaik untuk  ketebalan. Pada zona saprolit metode IDW dengan power 5 mempunyai performa terbaik untuk kadar Ni dan IDW power 1 menunjukkan performa terbaik pada kadar co dan ketebalan. Hasil interpolasi menunjukkan bahwa distribusi nikel dan potensi tambahan sumberdaya pada zona limonit dan saprolit masih terbuka ke arah timur laut dan barat daya daerah penelitian.Kata Kunci: ArcGIS, cross validation, IDW, OK, RMSE

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