A Random Forest Algorithm for Retrieving Canopy Chlorophyll Content of Wheat and Soybean Trained with PROSAIL Simulations Using Adjusted Average Leaf Angle

A Random Forest Algorithm for Retrieving Canopy Chlorophyll Content of Wheat and Soybean Trained with PROSAIL Simulations Using Adjusted Average Leaf Angle

Canopy chlorophyll content (CCC) is an important indicator for crop-growth monitoring and crop productivity estimation. The hybrid method, involving the PROSAIL radiative transfer model and machine learning algorithms, has been widely applied for crop CCC retrieval. However, PROSAIL’s homogeneous ca...

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Bibliographic Details
Main Authors: Quanjun Jiao, Qi Sun, Bing Zhang, Wenjiang Huang, Huichun Ye, Zhaoming Zhang, Xiao Zhang, Binxiang Qian
Format: Article
Language:English
Published: MDPI AG 2021-12-01
Series:Remote Sensing
Subjects:
crop chlorophyll
average leaf angle
PROSAIL
machine learning
red edge
radiative transfer model
Online Access:https://www.mdpi.com/2072-4292/14/1/98

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