A hybrid method for major food crops leaf chlorophyll content inversion driven by remote sensing mechanisms and deep learning

SHEN Yanyan; MENG Ran; LI Jiasheng; ZHAO Ping; ZHAO Feng; SUN Rui; ZHANG Hongyan; NI Xiang; LU Lijie; LIU Yong; LIU Jie

doi:10.11834/jrs.20265150

Forestry and Agriculture | Views:613Downloads:809CSCD:0

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A hybrid method for major food crops leaf chlorophyll content inversion driven by remote sensing mechanisms and deep learning
“The research team has constructed a leaf chlorophyll content inversion framework driven by both remote sensing mechanism and deep learning. By using a low leaf area index sensitive vegetation index ratio feature set and an active learning transfer strategy, the interference of canopy structure is effectively weakened, achieving high-precision cross crop monitoring of multiple staple crops such as corn, rice, wheat, and soybean. This provides a universal solution for non-destructive monitoring of crop physiology in multiple regions.”
- role：First author第一作者
- Affiliation：
  College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China
  National Key Laboratory of Smart Farm Technologies and Systems, Harbin 150000, China
- Email：shenyy_rs@163.com
- Introduction：沈艳艳，研究方向为农业遥感。E-mail：shenyy_rs@163.com
SHEN Yanyan
12 * ,
- role：Corresponding author通信作者
- Affiliation：
  National Key Laboratory of Smart Farm Technologies and Systems, Harbin 150000, China
  School of Computer Science and Technology, Institute for Artificial Intelligence, Harbin Institute of Technology, Harbin 150000, China
- Email：mengran@hit.edu.cn
- Introduction：孟冉，研究方向为农业遥感。E-mail：mengran@hit.edu.cn
MENG Ran
23 * ,
- Affiliation：
  School of Computer Science and Technology, Institute for Artificial Intelligence, Harbin Institute of Technology, Harbin 150000, China
LI Jiasheng
3 * ,
- Affiliation：
  College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China
  National Key Laboratory of Smart Farm Technologies and Systems, Harbin 150000, China
ZHAO Ping
12 * ,
- Affiliation：
  College of Forestry, Northeast Forestry University, Harbin 150000, China
ZHAO Feng
4 * ,
- Affiliation：
  College of Resources and Environment, Huazhong Agricultural University, Wuhan 430070, China
  National Key Laboratory of Smart Farm Technologies and Systems, Harbin 150000, China
SUN Rui
12 * ,
- Affiliation：
  Beidahuang Information Company Limited, Harbin 150000, China
ZHANG Hongyan
5 * ,
- Affiliation：
  Beidahuang Information Company Limited, Harbin 150000, China
NI Xiang
5 * ,
- Affiliation：
  National Key Laboratory of Smart Farm Technologies and Systems, Harbin 150000, China
  School of Computer Science and Technology, Institute for Artificial Intelligence, Harbin Institute of Technology, Harbin 150000, China
LU Lijie
23 * ,
- Affiliation：
  Beidahuang Information Company Limited, Harbin 150000, China
LIU Yong
5 * ,
- Affiliation：
  National Key Laboratory of Smart Farm Technologies and Systems, Harbin 150000, China
  School of Computer Science and Technology, Institute for Artificial Intelligence, Harbin Institute of Technology, Harbin 150000, China
LIU Jie
23 *
Vol. 30, Issue 5, Pages: 1392-1412(2026)
DOI：10.11834/jrs.20265150
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A hybrid method for major food crops leaf chlorophyll content inversion driven by remote sensing mechanisms and deep learning

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A hybrid method for major food crops leaf chlorophyll content inversion driven by remote sensing mechanisms and deep learning

SHEN Yanyan

MENG Ran

LI Jiasheng

ZHAO Ping

ZHAO Feng

SUN Rui

ZHANG Hongyan

NI Xiang

LU Lijie

LIU Yong

LIU Jie

DOI：10.11834/jrs.20265150

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