2022
DOI: 10.26833/ijeg.940997
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Determining the relationship between the slope and directional distribution of the UAV point cloud and the accuracy of various IDW interpolation

Abstract: Interpolation UAV point cloud Shepard Slope effect AnisotropyInverse Distance Weighted (IDW) based interpolation method is also widely used in earth science studies. In the classical IDW method, the directional distribution of the reference points around the point to be estimated within the critical circle and the slope differences are not taken into consideration. On the other hand, in the IDW-based method developed by Shepard, the ratio of the distances of the reference points within the critical circle to t… Show more

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Cited by 12 publications
(5 citation statements)
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“…As a result, it assigns higher weights to points that are near the prediction pg. 4 location, while the weights progressively decrease as a function of distance (Hastaoğlu et al, 2022). Figure 4 provides a visual representation of the weights assigned to the data points.…”
Section: Methodsmentioning
confidence: 99%
“…As a result, it assigns higher weights to points that are near the prediction pg. 4 location, while the weights progressively decrease as a function of distance (Hastaoğlu et al, 2022). Figure 4 provides a visual representation of the weights assigned to the data points.…”
Section: Methodsmentioning
confidence: 99%
“…It uses local interpolation since it only creates estimates from surrounding spots. The method is based on the notion that local points have a higher weight on the interpolated surface than remote points (Yılmaz and Kuru 2019;Hastaoğlu et al 2021).…”
Section: Inverse Distance Weighted Interpolation Methods (Idw)mentioning
confidence: 99%
“…Wang et al [ 27 ] used a radial basis function neural network (RBFNN) with spatial interpolation to achieve high accuracy in a UAV DSM. Hastaoglu et al [ 29 ] used an inverse distance weighted model (IDW) that took into account field slope and directional distributions of reference points in IDW-based interpolations to increase the accuracy of DTM. However, in a dense forest, it is not possible to derive an accurate DTM using photogrammetric methods, because insufficient ground surface is visible in the aerial images [ 24 , 25 , 26 ].…”
Section: Introductionmentioning
confidence: 99%