Application of Hyperspectral Technology for Crop Monitoring
A Special Issue of Agriculture (ISSN 2077-0472) belonging to the section "Artificial Intelligence and Digital Agriculture".
Deadline for manuscript submissions: 31 January 2027 | Viewed by 419
Editors
Interests: site-specific fertilizer management; using remote sensing data (satellite and drone images) for crop managements; using variouse spatial data (yield monitoring data, elevation data, soil data, RS data, soil test data) to describe spatial variability of production fields
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing in precision agriculture, plant phenotyping; geospatial analytics; image processing; photogrammetry
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing technology serves as a cornerstone of precision agriculture, providing the digitized data essential for digital farming. While multispectral imaging is highly effective at monitoring general crop vigor and detecting plant health anomalies, it lacks the diagnostic depth required to identify the underlying causes of unhealthiness.
In contrast, hyperspectral technology offers a specific approach. By collecting data across hundreds of narrow, contiguous spectral bands, it enables the identification of specific wavelengths associated with distinct biological or environmental stressors.
As smart agriculture—encompassing smart farms and automated greenhouses—continues to scale, there is an increasing demand for integrated digital systems. These systems must seamlessly collect, transfer, and analyze data to drive automated control mechanisms. Hyperspectral remote sensing is particularly critical in this system, as it provides the high-fidelity data necessary to trigger precise, autonomous actions.
This Special Issue explores the integration of hyperspectral systems within the smart agriculture framework, focusing on three primary areas:
- Diagnostic Capabilities: Assessing the potential of hyperspectral imaging to differentiate between specific crop stressors and detect peak ripeness in fruits and grapevines.
- Methodological Frameworks: Using hyperspectral technologies across diverse platforms—including handheld devices, ground-based robotics, and Unmanned Aerial Vehicles (UAVs).
- Systems Integration: Developing the technical bridge between hyperspectral data analytics and execution systems to enable real-time, automated responses in smart farming environments.
The topics of this Special Issue include (but are not limited to) the following:
- Hyperspectral sensors for crop plants;
- Hyperspectral sensors for fruits, grapevines, and vegetables;
- ML for hyperspectral data;
- Hyperspectral sensors for smart greenhouse;
- Hyperspectral sensors on robots and UAVs;
- Hyperspectral sensors and automations.
Dr. Jiyul Chang
Dr. Maitiniyazi Maimaitijiang
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. 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
- hyperspectral sensors
- smart agriculture
- crop monitoring
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