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The New England Journal of Statistics in Data Science


Irrigation Zone Delineation by Coupling Neural Networks with Spatial Statistics
Volume 3, Issue 1 (2025), pp. 82–93
Pub. online: 31 October 2024      Type: Methodology Article      Open accessOpen Access
Area: Spatial and Environmental Statistics
Accepted
21 August 2024
Published
31 October 2024

Abstract

Variable rate irrigation (VRI) seeks to increase the efficiency of irrigation by spatially adjusting water output within an agricultural field. Central to the success of VRI technology is establishing homogeneous irrigation zones. In this research, we propose a fusion of statistical modeling and deep learning by using artificial neural networks to map irrigation zones from simple-to-measure predictors. We further couple our neural network model with spatial correlation to capture smooth variations in the irrigation zones. We demonstrate the effectiveness of our model to define irrigation zones for a farm of winter wheat crop in Rexburg, Idaho.

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© 2025 New England Statistical Society
Open access article under the CC BY license.

Keywords
Ordered multinomial Precision agriculture Bayesian

Funding
This work was partially funded by the US-Israel Binational Agricultural Research and Development Fund grant IS-5218-19.

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