Remote and Proximal Sensing for Arable Crops Monitoring and Yield Assessment
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Artificial Intelligence and Digital Agriculture".
Deadline for manuscript submissions: 31 December 2026 | Viewed by 2
Special Issue Editors
Interests: remote sensing; UAV; satellite data; precision agriculture; GIS; geospatial analysis
Special Issues, Collections and Topics in MDPI journals
Interests: irrigation; hydrology; water resources
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote and proximal sensing technologies have rapidly transformed arable crop monitoring over the last two decades, evolving from simple spectral index analysis to sophisticated multi-sensor, multi-scale, and AI-driven approaches. Recent advancements in satellite missions, UAV multispectral/thermal imaging, LiDAR, proximal canopy sensors, and soil–plant–atmosphere monitoring systems have enabled unprecedented spatial and temporal detail in assessing crop conditions, stress responses, and yield formation processes.
This Special Issue aims to bring together cutting-edge research that leverages Earth observation, field-based sensing, artificial intelligence, and data-fusion methodologies to improve crop monitoring, input optimization, and yield assessment in arable systems. We invite contributions showcasing methodological innovations, operational applications, and integrative frameworks that support sustainable crop production and precision agriculture.
We particularly welcome studies that combine multi-scale datasets, exploit machine learning or deep learning models, develop decision-support tools, or demonstrate real-world implementations.
We seek original research articles, technical developments, reviews, and case studies covering remote sensing, proximal sensing, AI analytics, data fusion, variable-rate applications, and yield prediction for major arable crops (e.g., cereals, cotton, maize, legumes). Submissions addressing climate-smart agriculture, resource-efficient management, and regional upscaling of field-level monitoring approaches are especially encouraged.
Dr. Emmanouil Psomiadis
Prof. Dr. Nicholas Dercas
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
- remote sensing
- proximal sensing
- UAV multispectral/thermal imaging
- LiDAR
- vegetation indices
- crop monitoring
- yield assessment
- data fusion
- artificial intelligence
- machine learning
- precision agriculture
- digital agriculture
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