Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices?

Leveraging Spectral Neighborhood Information for Corn Yield Prediction with Spatial-Lagged Machine Learning Modeling: Can Neighborhood Information Outperform Vegetation Indices?

Accurate and reliable crop yield prediction is essential for optimizing agricultural management, resource allocation, and decision-making, while also supporting farmers and stakeholders in adapting to climate change and increasing global demand. This study introduces an innovative approach to crop y...

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Bibliographic Details
Main Authors: Efrain Noa-Yarasca, Javier M. Osorio Leyton, Chad B. Hajda, Kabindra Adhikari, Douglas R. Smith
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:AI
Subjects:
corn yield prediction
spatial-lagged machine learning model
spectral neighborhood data
vegetation indices (VIs)
spatial autocorrelation
Online Access:https://www.mdpi.com/2673-2688/6/3/58
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