A Weighted Radial Basis Function Interpolation Method for High Accuracy DEM Modeling

GAO Yuan; ZHU Yanan; CHEN Chuanfa; HU Zhanzhan; HU Baojian

doi:10.13203/j.whugis20210100

Volume 48 Issue 8

Aug. 2023

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Geomatics and Information Science of Wuhan University > 2023 > 48(8): 1373-1379. > DOI: 10.13203/j.whugis20210100

GAO Yuan, ZHU Yanan, CHEN Chuanfa, HU Zhanzhan, HU Baojian. A Weighted Radial Basis Function Interpolation Method for High Accuracy DEM Modeling[J]. Geomatics and Information Science of Wuhan University, 2023, 48(8): 1373-1379. DOI: 10.13203/j.whugis20210100

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A Weighted Radial Basis Function Interpolation Method for High Accuracy DEM Modeling

1.
College of Geomatics, Shandong University of Science and Technology, Qingdao 266590, China
2.
Jinan Real Estate Registration Center, Jinan 250000, China

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Received Date: September 02, 2021
Available Online: August 02, 2023
Published Date: August 04, 2023

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Abstract

Objectives In the process of digital elevation model (DEM) modeling, the existing interpolation methods do not take into account the local topographic characteristics near the breaklines, which makes the elevation of the local area of the breakline smoothed, thus leading to topographic distortion. A weight function with respect to considering the characteristics of breaklines is constructed, and a weight radial basis function (RBF) method is proposed. The proposed method makes full use of the gradient and direction information of the sampling points near the fracture line.
Methods First, the distance between the sampling point and the point to be sought is calculated adaptively by capturing the structure tensor of each sampling point, and then the distance is used to assign a suitable weight to each sampling point, finally the DEM modeling is realized by using weighted interpolation.
Results Examples on 10 public data and 1 private dataset of DEM construction with airborne light detection and ranging (LiDAR) point clouds indicates that the calculation results of each interpolation method gradually decrease with the decrease of sampling points. Compared to RBF and the classical interpolation methods including inverse distance weighting, ordinary Kriging and constrained triangulated irregular network, our proposed method has a better ability to maintain terriain features in the breakline area. Regardless of sample density, our proposed method is always more accurate than the other methods.
Conclusions Overall, the proposed method with the merit of terrain feature preservation is helpful for the construction of high-accurate DEMs, which play an important role in some geoscience applications with data quality as the most important factor.
- digital elevation model,
- breakline,
- radial basis function,
- interpolation,
- airborne LiDAR point cloud

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A Weighted Radial Basis Function Interpolation Method for High Accuracy DEM Modeling

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