Enhanced Crop Leaf Area Index Estimation via Random Forest Regression: Bayesian Optimization and Feature Selection Approach

Enhanced Crop Leaf Area Index Estimation via Random Forest Regression: Bayesian Optimization and Feature Selection Approach

The Leaf Area Index (LAI) is a crucial structural parameter linked to the photosynthetic capacity and biomass of crops. While integrating machine learning algorithms with spectral variables has improved LAI estimation over large areas, excessive input parameters can lead to data redundancy and reduc...

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Bibliographic Details
Main Authors: Jun Zhang, Jinpeng Cheng, Cuiping Liu, Qiang Wu, Shuping Xiong, Hao Yang, Shenglong Chang, Yuanyuan Fu, Mohan Yang, Shiyu Zhang, Guijun Yang, Xinming Ma
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Remote Sensing
Subjects:
leaf area index
hyperparameter optimization
Bayesian algorithm
random forests
Online Access:https://www.mdpi.com/2072-4292/16/21/3917
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