Innovative Remote Sensing Technologies in Precision Agriculture
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Agricultural Science and Technology".
Deadline for manuscript submissions: 30 December 2025 | Viewed by 9
Special Issue Editors
Interests: agriculture remote sensing; biochemical and biophysical parameters estimation; yield estimation
Special Issues, Collections and Topics in MDPI journals
Interests: technologies in soil spectroscopy; innovations and techniques in soil and plant analysis; non-destructive techniques for soil testing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Recent advances in remote sensing technologies have revolutionized precision agriculture by enabling the high-resolution, real-time monitoring of crop and soil conditions. Innovations in satellite, UAV (unmanned aerial vehicle), and ground-based sensor systems have provided farmers with multispectral, hyperspectral, LiDAR, and thermal imaging capabilities, allowing them to assess vegetation health, moisture levels, nutrient deficiencies, and pest and disease infestations with unprecedented accuracy. Artificial intelligence algorithms integrated with these datasets facilitate predictive analytics for yield optimization, irrigation management, and targeted resource application (e.g., fertilizers, pesticides), reducing environmental impacts while maximizing productivity.
This Special Issue welcomes papers on advances in remote sensing for precision agriculture. Topics include, but are not limited to, biochemical and biophysical parameter estimation, soil condition monitoring, yield estimation, pest and disease forecasting, artificial intelligence, novel proximal sensors, and the recent application of multispectral, hyperspectral, LiDAR, SAR, and thermal remote sensing in crop monitoring.
Dr. Weiping Kong
Prof. Dr. Pantelis E. Barouchas
Guest Editors
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Keywords
- artificial intelligence algorithms
- yield estimation
- biochemical and biophysical parameters estimation
- soil condition monitoring
- vegetation remote sensing product validation
- commercial crops, grass, and other crops
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