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Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation

Author

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  • Luis Pastor Sánchez-Fernández

    (Centro de Investigación en Computación, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, Mexico City 07738, Mexico)

  • Diego Alberto Flores-Carrillo

    (Centro de Investigación en Computación, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, Mexico City 07738, Mexico)

  • Luis Alejandro Sánchez-Pérez

    (Department of Electrical and Computer Engineering, University of Michigan, Dearborn, MI 48126, USA)

Abstract

In this paper, an intelligent weather conditions fuzzy adjustment based on spatial features (IWeCASF) is developed. It is indispensable for our regional soil moisture estimation approach, complementing a point estimation model of soil moisture from the literature. The point estimation model requires the weather conditions at the point where an estimate is made. Therefore, IWeCASF’s aim is to determine these weather conditions. The procedure begins measuring them at only one checkpoint, called the primary checkpoint. The model determines the weather conditions anywhere within a region through image processing algorithms and fuzzy inference systems. The results are compared with the measurement records and with a spatial interpolation method. The performance is similar to or better than interpolation, especially in the rain, where the model developed is more accurate due to the certainty of replication. Additionally, IWeCASF does not require more than one measurement point. Therefore, it is a more appropriate approach to complement the point estimation model for enabling a regional soil moisture estimation.

Suggested Citation

  • Luis Pastor Sánchez-Fernández & Diego Alberto Flores-Carrillo & Luis Alejandro Sánchez-Pérez, 2024. "Computer Model for an Intelligent Adjustment of Weather Conditions Based on Spatial Features for Soil Moisture Estimation," Mathematics, MDPI, vol. 12(1), pages 1-33, January.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:1:p:152-:d:1312235
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    References listed on IDEAS

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    2. Jaenam Lee, 2022. "Evaluation of Automatic Irrigation System for Rice Cultivation and Sustainable Agriculture Water Management," Sustainability, MDPI, vol. 14(17), pages 1-12, September.
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