Advancements in Remote Sensing and AI-Driven Analytics for Sustainable Agriculture
A special issue of AgriEngineering (ISSN 2624-7402). This special issue belongs to the section "Computer Applications and Artificial Intelligence in Agriculture".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 469
Special Issue Editors
Interests: image processing; data visualization; remote sensing
Interests: digital agriculture; phenomics; horticulture
Special Issue Information
Dear Colleagues,
The agricultural sector is rapidly evolving via the integration of advanced technologies such as remote sensing and artificial intelligence (AI). By harnessing the power of satellite imagery, drones, and sensor networks, coupled with AI-driven analytics, farmers are able to monitor environmental conditions, track crop health, and make data-driven decisions with greater accuracy and efficiency. Remote sensing provides detailed, large-scale data, while machine learning and deep learning algorithms process this information to offer predictive insights regarding crop yield, pest detection, irrigation management, and disease prevention. These innovations enable precision farming, where the utilization of resources is optimized, the quality of crops is enhanced, and environmental impacts are minimized.
As the global agricultural landscape faces challenges posed by climate change, resource scarcity, and a growing demand for food, AI and remote sensing technologies offer solutions that promote sustainable farming practices. AI-based models such as reinforcement learning and optimization algorithms are revolutionizing crop management, pest control, and irrigation systems, enhancing both economic and environmental sustainability.
This Special Issue aims to highlight the latest advancements in the application of remote sensing and AI-driven analytics in agriculture. The scope of this Special Issue includes, but is not limited to, the following topics:
- Remote sensing for crop monitoring
- Machine learning and deep learning in agriculture
- Precision farming and resource optimization
- AI-driven pest and disease management
- IoT and sensor networks in agriculture
- Data-driven agriculture and climate adaptation
- Sustainable agricultural practices
- Agricultural robotics and automation
Dr. Feiyu Zhu
Dr. Xia Qiu
Guest Editors
Manuscript Submission Information
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Keywords
- remote sensing
- artificial intelligence (AI)
- precision agriculture
- machine learning
- deep learning
- sustainable agriculture
- crop monitoring
- smart farming
- IoT and sensor networks
- agricultural optimization
- climate-resilient farming
- AI in pest and disease management
- data-driven farming
- agricultural robotics
- environmental sustainability
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