Recent Advances in Remote Sensing, Image Processing, and Deep Learning for Precision Agriculture
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".
Deadline for manuscript submissions: 30 June 2026 | Viewed by 9
Special Issue Editors
Interests: machine learning; remote sensing image processing; smart agriculture
Special Issue Information
Dear Colleagues,
Precision agriculture is undergoing a vital transformation, driven by the synergistic advancements in remote sensing, image processing, and deep learning. As the global demand for food increases amid climate change and limited resources, the need for efficient, sustainable, and data-driven farming practices has never been greater.
Remote sensing, from satellite imagery to drone-mounted sensors, provides a wealth of data on crop health, soil conditions, and environmental factors. However, extracting actionable insights from these complex data demands sophisticated methods. Deep learning, particularly CNNs and RNNs, excels at identifying subtle patterns in image data, enabling tasks such as disease detection, yield prediction, and nutrient assessment.
This Special Issue will collect high-quality papers presenting novel remote sensing techniques for early stress detection, advanced image processing for phenological monitoring, the application of deep learning for automated crop management, etc. Thus, this Special Issue is open to anyone who wants to submit a relevant research manuscript.
Dr. Yang-Jun Deng
Dr. Jinling Liu
Guest Editors
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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. Plants 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 2700 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
- precision agriculture technology
- agricultural remote sensing image processing
- deep learning/AI for agricultural information analysis
- remote sensing for crop monitoring
- yield prediction
- plant phenotype
- pest and disease detection and identification
- soil health management via deep learning, remote sensing, etc.
- intelligent breeding technology
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