Geoscientific Model Development
Geoscientific Model Development
GMD
Articles | Volume 16, issue 10
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.
https://doi.org/10.5194/gmd-16-2777-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
Articles | Volume 16, issue 10
Development and technical paper
 | 
24 May 2023
Development and technical paper |  | 24 May 2023

A generalized spatial autoregressive neural network method for three-dimensional spatial interpolation

Junda Zhan, Sensen Wu, Jin Qi, Jindi Zeng, Mengjiao Qin, Yuanyuan Wang, and Zhenhong Du

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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.
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