Abstract:
Objective Three-dimensional landslide deformation data are usually characterized by pronounced anisotropy because of terrain undulation, geological structure, and sliding processes. Existing anisotropy-aware interpolation methods can represent directional differences, but their model construction and parameter settings are relatively complex. Inverse Distance Weighting (IDW) is simple and computationally efficient; however, its isotropic assumption limits its direct application to anisotropic landslide deformation data. To address this issue, this study proposes a Data-Oriented Anisotropic IDW (DOA-IDW) method for reconstructing the 3D vector spatial field of landslide deformation.
Methods The proposed method performs anisotropy analysis on 3D landslide deformation data and constructs a rotation-stretch matrix to transform the original anisotropic space into a near-isotropic space, allowing IDW interpolation to be conducted in an approximately isotropic coordinate system and thereby improving interpolation accuracy. Experiments were carried out on the Baobaocun landslide in Dongchuan District, Kunming, Yunnan Province.
Results Compared with IDW, Searching Elliptical Range Anisotropic IDW (SERI-IDW), Anisotropic Radial Basis Function (ARBF), and Anisotropic Kriging (AK), DOA-IDW performs better in terms of Root Mean Square Error (RMSE), Mean Absolute Error (MAE), and related metrics; RMSE and MAE are reduced by 3.1%～11.5% and 3.1%～11.3%, respectively. The DOA-IDW reconstruction is also generally consistent with the 3D real-scene model and InSAR results and can better reflect the magnitude, direction, and spatial distribution of landslide deformation in the study area.
Conclusion DOA-IDW effectively accounts for anisotropy in 3D landslide deformation data and improves the reconstruction accuracy of the 3D vector spatial field of landslide deformation.
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