Multi-Source Sensing and Advanced Image Analysis in Plant Sciences
A special issue of Plants (ISSN 2223-7747). This special issue belongs to the section "Plant Modeling".
Deadline for manuscript submissions: 31 August 2027
Editors
Interests: precision agriculture; deep learning; remote sensing; plant phenotyping; smart breeding
Special Issues, Collections and Topics in MDPI journals
Interests: non-destructive crop growth monitoring; smart agricultural decision-making; agricultural big data; AI in agriculture
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The rapid evolution of sensing technologies and computer vision has revolutionized the way we monitor plant growth, health, and physiological status. Moving beyond traditional remote sensing, modern agricultural and botanical research now integrates a spectrum of observation scales from spaceborne and aerial platforms to close-range ground sensors and handheld imaging devices. This Special Issue aims to provide a comprehensive platform for discussing the fusion of multi-source sensing data and the application of advanced image analysis techniques in plant sciences.
We invite researchers and practitioners to contribute original research articles and review papers that explore innovative methodologies for multi-scale plant monitoring, addressing, but not limited to, cross-platform data fusion, deep learning-based image processing, automated phenotyping, stress detection, and the development of intelligent sensing systems. Our goal is to bridge the gap between technical sensing innovations and practical applications in plant research, fostering a deeper understanding of plant dynamics across diverse environmental conditions. Articles may include, but are not limited to, the following topics:
- Multi-Scale Data Fusion: Integration of satellite, UAV, and ground-based or handheld sensor data for comprehensive plant monitoring.
- Advanced Image Analysis: Application of deep learning, convolutional neural networks, vision transformers, and classical computer vision in processing plant imagery.
- Plant Phenotyping: Automated and high-throughput phenotyping techniques for analyzing morphological, physiological, and biochemical plant traits.
- Stress and Health Assessment: Intelligent detection of abiotic stresses such as drought, salinity, and nutrient deficiency as well as biotic stresses like pests and diseases.
- Intelligent Sensing Systems: Development and deployment of low-cost sensors, Internet of Things based monitoring, and innovative hardware solutions for plant data acquisition.
- Growth and Yield Modeling: Predictive modeling of plant development, biomass estimation, and yield forecasting using multi-source data.
- Smart Agriculture and Forestry: Applications of multi-source sensing and image analysis in precision agriculture, smart forestry, and ecological monitoring.
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized 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
- plant monitoring
- multi-scale data fusion
- image analysis
- precision agriculture
- deep learning
- plant phenotyping
- remote sensing
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