Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning

Research on the Inversion of Key Growth Parameters of Rice Based on Multisource Remote Sensing Data and Deep Learning

This study accurately inverts key growth parameters of rice, including Leaf Area Index (LAI), chlorophyll content (SPAD) value, and height, by integrating multisource remote sensing data (including MODIS and ERA5 imagery) and deep learning models. Dehui City in Jilin Province, China, was selected as...

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Bibliographic Details
Main Authors: Jian Li, Jian Lu, Hongkun Fu, Wenlong Zou, Weijian Zhang, Weilin Yu, Yuxuan Feng
Format: Article
Language:English
Published: MDPI AG 2024-12-01
Series:Agriculture
Subjects:
multisource remote sensing data
deep learning
LSTM
crop growth parameter inversion
Online Access:https://www.mdpi.com/2077-0472/14/12/2326
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