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Recent Methods for Evaluating Crop Water Stress Using AI Techniques: A Review
Soo Been Cho1, Hidayat Mohamad Soleh1, Ji Won Choi1
1Department of Biosystems Engineering, College of Agricultural and Life Sciences, Gyeongsang National University, 501, Jinju-daero, Jinju-si 52828, Gyeongsangnam-do, Republic of Korea.
Sensors (Basel, Switzerland)
|October 16, 2024
Summary
This study reviews artificial intelligence (AI) and remote sensing for crop water stress monitoring. These technologies help improve agricultural productivity and mitigate climate change impacts on crops.
Area of Science:
- Agricultural Science
- Environmental Science
- Computer Science
Background:
- Rising global temperatures and climate change exacerbate crop water stress.
- Variability in precipitation patterns poses significant challenges to agricultural productivity.
- Effective monitoring and prediction of crop water stress are crucial for sustainable agriculture.
Purpose of the Study:
- To systematically review the integration of artificial intelligence (AI) and remote sensing technologies for crop water stress management.
- To evaluate the effectiveness of various non-destructive remote sensing platforms and AI techniques in monitoring and predicting crop water stress.
- To explore strategic combinations of these technologies under data-limited conditions to enhance agricultural productivity.
Main Methods:
- Systematic literature review of AI and remote sensing integration in agriculture.
- Analysis of non-destructive remote sensing platforms: RGB, thermal, and hyperspectral imaging.
- Evaluation of AI techniques: machine learning, deep learning, ensemble methods, GAN, and XAI.
Main Results:
- AI and remote sensing offer effective, non-destructive methods for monitoring crop water stress.
- Different platforms and AI techniques show varying strengths in accuracy and applicability.
- Strategic integration can enhance crop water stress prediction, even with limited data.
Conclusions:
- The integration of AI and remote sensing is vital for addressing climate change impacts on agriculture.
- These technologies provide tools for improving crop yield and quality under water stress.
- Further research can optimize combined approaches for resilient and sustainable farming systems.
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