Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection

Estimating Leaf Chlorophyll Fluorescence Parameters Using Partial Least Squares Regression with Fractional-Order Derivative Spectra and Effective Feature Selection

Chlorophyll fluorescence (ChlF) parameters serve as non-destructive indicators of vegetation photosynthetic function and are widely used as key input parameters in photosynthesis–fluorescence models. The rapid acquisition of the spatiotemporal dynamics of ChlF parameters is crucial for enhancing rem...

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Bibliographic Details
Main Authors: Jie Zhuang, Quan Wang
Format: Article
Language:English
Published: MDPI AG 2025-02-01
Series:Remote Sensing
Subjects:
chlorophyll fluorescence
feature selection
fractional-order derivative
hyperspectral
partial least squares regression
Online Access:https://www.mdpi.com/2072-4292/17/5/833
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