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December 8, 2025AgriEngineeringOpen Access

Study on the Retrieval of Leaf Area Index for Summer Maize Based on Hyperspectral Data

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TZTian Zhang

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Overview

Monitoring changes in leaf area index in summer maize indicates the impact of planting dates and climate stress.

Key Points

  • This research aims to estimate leaf area index (LAI) for summer maize using hyperspectral data to address climate change effects.
  • Examines summer maize across different planting dates in North China Plain
  • Uses stepwise regression analysis, multiple vegetation indices, and fractional order derivatives
  • Employs algorithms such as Random Forest and Partial Least Squares Regression for LAI inversion modeling
  • Dual-band combination vegetation indices show strong correlation with summer maize LAI
  • Ensemble learning algorithms like Random Forest achieve average R2 values of 0.93
  • Model accuracy significantly decreases for delayed planting and varies across planting dates

Cite This Study

Tian Zhang (2025) studied this question.

synapsesocial.com/papers/693624ce4fa91c937236cdc4https://doi.org/10.3390/agriengineering7120418
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  5. 5Generalization of peanut yield prediction models using artificial neural networks and vegetation indices2025 · 4 citations