Comparative Analysis of the Digital Terrain Models Created from Ground Surveying Measurements with the Use of Different Ordinary Kriging Models | ||||
| Engineering Research Journal | ||||
| Volume 180, Issue 0, December 2023, Page 329-243 PDF (930.03 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erj.2023.331005 | ||||
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| Author | ||||
| Fahmy Fahim Fahmy Asal* | ||||
| Civil Engineering Department, Faculty of Engineering, Menoufia University, Egypt, | ||||
| Abstract | ||||
| Digital Terrain Model (DTM) is a continuous surface containing ground elevation values as well as other elements describing the topographic surface such as slope, aspect, curvature, etc. DTM is created from discrete elevation data through an interpolation operation. Ordinary Kriging methods are geostatistical approaches that incorporate spatial autocorrelation and generate estimated surfaces from scattered sets of points through minimizing the errors between the predicted values and the statistical model of the surface (Maune and Nayegandhi, 2018). This research aimed at comparative analysis of the DTMs created from ground surveying digital elevation data through exploitation of the different models of the ordinary kriging. DTMs have been created from ground surveying sample data using t ordinary kriging models. Statistical analysis of the DTMs indicated that Gaussian model DTM depicts the smallest standard deviation of elevations. Additionally, the spherical, linear, circular, and exponential model DTMs achieve standard deviations of elevations of 101.99%, 102.21%, 102.40% and 102.43% of the standard deviation of elevations given by the Gaussian model DTM, respectively. Moreover, statistical analysis of the elevation residuals extracted from the different DTMs using external checkout points shows that the DTM from the Gaussian model achieve the highest standard deviation of elevation residuals which refers to the lowest accuracy DTM. Thus, the DTMs from the linear, spherical, circular, and exponential models achieve smaller and remarkably closestandard deviation of elevation residuals that are about 80.83%, 80.88%, 81.11% and 81.3% respectively of the standard deviation of elevation residuals achieved by the Gaussian DTM model. | ||||
| Keywords | ||||
| DTM; Geostatistical interpolation; Ordinary Kriging Models; Visual Analysis; Accuracy Analysis | ||||
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