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From detection to decision: AI-driven remote sensing for abiotic stress management
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DOI：10.1016/j.agsy.2026.104908.png)
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Abstract
En 中文
• Links stress physiology to multi-scale remote sensing. • Evaluates deep learning for cross-platform data fusion. • Bridges AI detection with variable-rate interventions. • Identifies ground truth scarcity and causality gaps. • Proposes framework for farmer-centric stress management.
Keywords:
Abiotic stress
Remote sensing
Machine learning
Decision support systems
Precision agriculture
Climate adaptation
AI
,
Artificial Intelligence
CNN
,
Convolutional Neural Network
CWSI
,
Crop Water Stress Index
DMS
,
Data Mining Sharpener
IoT
,
Internet of Thing
LiDAR
,
Light Detection and Ranging
SHAP
,
SHapley Additive exPlanation
UAV
,
Unmanned Aerial Vehicle
ViT
,
Vision Transformer
XAI
,
eXplainable AI
Journal
IF:
6.1
Papers:
3.8K
Citations:
1.4W
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