Remote Sensing Technologies in Crop Monitoring and Plant Phenotyping
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".
Deadline for manuscript submissions: 31 July 2026 | Viewed by 6
Special Issue Editors
Interests: precision agriculture; deep learning; remote sensing; plant phenotyping; breeding
Interests: non-destructive crop growth monitoring; smart agricultural decision-making; agricultural big data; AI in agriculture
Special Issue Information
Dear Colleagues,
Remote sensing technologies have become indispensable tools in modern agriculture and plant science, offering rapid, non-invasive, and scalable approaches to monitor crops and quantify plant traits. This Special Issue aims to highlight recent advances in remote sensing applications for crop monitoring and plant phenotyping, with a focus on both fundamental research and practical implementation. Topics of interest include UAV and satellite-based imaging, multispectral and hyperspectral sensing, LiDAR, thermal imaging, and the integration of AI for data analysis. We welcome studies that explore dynamic crop growth monitoring, stress detection, yield estimation, and trait mapping across spatial and temporal scales. Submissions may also address sensor innovation, data fusion, and phenotyping frameworks to support breeding, cultivation management, and precision agriculture. The goal is to promote interdisciplinary research that bridges remote sensing, plant biology, and agronomy to improve crop productivity and sustainability. Articles may include, but are not limited to, the following topics:
- UAV, satellite, and ground-based imaging for crop monitoring;
- High-throughput phenotyping using imaging technologies;
- Remote sensing of plant growth, stress, and health status;
- Yield prediction based on time-series remote sensing data;
- Integration of AI and deep learning for trait extraction;
- Multi-source data fusion for improved crop analysis;
- Sensor development and calibration for field phenotyping;
- Remote sensing applications in breeding and variety evaluation;
- Disease and pest detection using remote imagery;
- Time-series analysis of vegetation dynamics and phenological stages.
Dr. Qing Gu
Dr. Yuan Wang
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
- remote sensing
- crop monitoring
- plant phenotyping
- trait analysis
- precision agriculture
- smart breeding
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