Remote Sensing in Crop Protection
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Artificial Intelligence and Digital Agriculture".
Deadline for manuscript submissions: 30 March 2026 | Viewed by 58
Special Issue Editors
Interests: Internet of Things (IoT); sensors; electronics; information and communication technologies (ICT); data analysis; deep learning; classification; clustering analysis; precision agriculture
Special Issues, Collections and Topics in MDPI journals
Interests: modern agriculture technologies; smart greenhouses; smart vegetable growing; crop monitoring; precision farming; farm automation; remote sensing; data-driven farming
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid advancement of remote sensing technologies and artificial intelligence has opened many new opportunities for the precise monitoring and control of crop production. The combined application of drones, satellites, different spectrum sensors, machine learning, and deep learning enables the optimization of crop protection by introducing the early identification of pests and diseases, smart application of pesticides, etc. Together, these innovations support higher yields, improved resource efficiency, and more resilient farming systems.
This Special Issue invites contributions that explore the application of the abovementioned technologies in all areas of crop protection. We welcome original research articles, reviews, and case studies on (but not limited to) the following:
- Remote sensing for crop protection;
- Machine learning- and deep learning-enhanced crop protection;
- Early identification of pests and diseases;
- Analysis of UAV-obtained and satellite-obtained data;
- Pest identification-based on vegetation indices;
- Cloud computing and decision support systems for smart crop protection.
We encourage researchers and practitioners to share their latest findings, innovations, and practical applications that drive the digital transformation and sustainability of crop protection.
Prof. Dr. Boris Evstatiev
Dr. Atanas Atanasov
Guest Editors
Manuscript Submission Information
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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Agriculture is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
Keywords
- satellite
- drone
- unmanned aerial vehicles (UAVs)
- machine learning
- deep learning
- artificial intelligence (AI)
- remote sensing
- cloud computing
- information systems
- crop protection
- vegetation indices
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