Articles | Volume 16, issue 10
https://doi.org/10.5194/gmd-16-2777-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/gmd-16-2777-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
A generalized spatial autoregressive neural network method for three-dimensional spatial interpolation
Junda Zhan
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
Sensen Wu
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
Zhejiang Provincial Key Laboratory of Geographic Information Science,
Hangzhou 310028, China
Jin Qi
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
Zhejiang Provincial Key Laboratory of Geographic Information Science,
Hangzhou 310028, China
Jindi Zeng
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
Mengjiao Qin
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
Zhejiang Provincial Key Laboratory of Geographic Information Science,
Hangzhou 310028, China
Yuanyuan Wang
Ocean Academy, Zhejiang University, Zhoushan 316022, China
Zhejiang Provincial Key Laboratory of Geographic Information Science,
Hangzhou 310028, China
Zhenhong Du
CORRESPONDING AUTHOR
School of Earth Sciences, Zhejiang University, Hangzhou 310027, China
Zhejiang Provincial Key Laboratory of Geographic Information Science,
Hangzhou 310028, China
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Cited
13 citations as recorded by crossref.
- Scalable spatio-temporal autoregressive modeling by designing equivalent graph convolutional neural networks H. Zhang & G. Dong https://doi.org/10.1080/13658816.2025.2526041
- Multipath Mitigation for Indoor Positioning with Empirical Mode Decomposition and Spatial Autoregressive Neural Network Methods Y. Yao et al. https://doi.org/10.1007/s11277-026-11939-z
- Optimal Mapping of Soil Texture Fractions: Two-Stage Hybrid Geostatistical and Machine Learning Models Outperform Individual Approaches in the Sistan Plain A. Bameri et al. https://doi.org/10.1134/S1064229326600752
- Complex network-constrained regional estimation of crop evapotranspiration using ERA5-Land data at meteorological station locations Y. Li et al. https://doi.org/10.1016/j.agwat.2026.110837
- DKNN: deep kriging neural network for interpretable geospatial interpolation K. Chen et al. https://doi.org/10.1080/13658816.2024.2347316
- A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution S. Miao et al. https://doi.org/10.1371/journal.pone.0316940
- AnywhereXR: on-the-fly 3D environments as a basis for open source immersive digital twin applications A. Klippel et al. https://doi.org/10.1080/17538947.2025.2520000
- Spatial Data Prediction Model Integrated with K-Nearest Neighbor Mechanism in Neural Networks X. Song et al. https://doi.org/10.1142/S0218001424580035
- On Grain Security by Temperature Interpolation: A Deep Learning Method for Comprehensive Data Fusion in Smart Granaries Z. Qu et al. https://doi.org/10.1109/TIM.2024.3485435
- A spatiotemporal autoregressive neural network interpolation method for discrete environmental factors J. Qi et al. https://doi.org/10.1016/j.envsoft.2024.106289
- An Improved Interpolation Algorithm for Surface Meteorological Observations via Fuzzy Adaptive Optimisation Fusion X. Jiang et al. https://doi.org/10.3390/atmos16070844
- GIS‐Based Land Evaluation and Suitability Analysis to Optimize Maize (Zea mays L.) Production in the Dura Watershed, Northern Ethiopia S. Fissaha et al. https://doi.org/10.1155/aia/9492681
- An Efficient Particle-Field Algorithm with Neural Interpolation Based on a Parabolic-Hyperbolic Chemotaxis System in 3D J. Kim & J. Xin https://doi.org/10.4208/nmtma.OA-2025-0127
13 citations as recorded by crossref.
- Scalable spatio-temporal autoregressive modeling by designing equivalent graph convolutional neural networks H. Zhang & G. Dong https://doi.org/10.1080/13658816.2025.2526041
- Multipath Mitigation for Indoor Positioning with Empirical Mode Decomposition and Spatial Autoregressive Neural Network Methods Y. Yao et al. https://doi.org/10.1007/s11277-026-11939-z
- Optimal Mapping of Soil Texture Fractions: Two-Stage Hybrid Geostatistical and Machine Learning Models Outperform Individual Approaches in the Sistan Plain A. Bameri et al. https://doi.org/10.1134/S1064229326600752
- Complex network-constrained regional estimation of crop evapotranspiration using ERA5-Land data at meteorological station locations Y. Li et al. https://doi.org/10.1016/j.agwat.2026.110837
- DKNN: deep kriging neural network for interpretable geospatial interpolation K. Chen et al. https://doi.org/10.1080/13658816.2024.2347316
- A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution S. Miao et al. https://doi.org/10.1371/journal.pone.0316940
- AnywhereXR: on-the-fly 3D environments as a basis for open source immersive digital twin applications A. Klippel et al. https://doi.org/10.1080/17538947.2025.2520000
- Spatial Data Prediction Model Integrated with K-Nearest Neighbor Mechanism in Neural Networks X. Song et al. https://doi.org/10.1142/S0218001424580035
- On Grain Security by Temperature Interpolation: A Deep Learning Method for Comprehensive Data Fusion in Smart Granaries Z. Qu et al. https://doi.org/10.1109/TIM.2024.3485435
- A spatiotemporal autoregressive neural network interpolation method for discrete environmental factors J. Qi et al. https://doi.org/10.1016/j.envsoft.2024.106289
- An Improved Interpolation Algorithm for Surface Meteorological Observations via Fuzzy Adaptive Optimisation Fusion X. Jiang et al. https://doi.org/10.3390/atmos16070844
- GIS‐Based Land Evaluation and Suitability Analysis to Optimize Maize (Zea mays L.) Production in the Dura Watershed, Northern Ethiopia S. Fissaha et al. https://doi.org/10.1155/aia/9492681
- An Efficient Particle-Field Algorithm with Neural Interpolation Based on a Parabolic-Hyperbolic Chemotaxis System in 3D J. Kim & J. Xin https://doi.org/10.4208/nmtma.OA-2025-0127
Saved (final revised paper)
Latest update: 05 Nov 2026
Short summary
We develop a generalized spatial autoregressive neural network model used for three-dimensional spatial interpolation. Taking the different changing trend of geographic elements along various directions into consideration, the model defines spatial distance in a generalized way and integrates it into the process of spatial interpolation with the theories of spatial autoregression and neural network. Compared with traditional methods, the model achieves better performance and is more adaptable.
We develop a generalized spatial autoregressive neural network model used for three-dimensional...
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