AI UAV-Based Systems for Agricultural Monitoring

Dear Colleagues,

Agricultural systems worldwide face increasing pressures from climate change, resource scarcity, and the demand for sustainable intensification. Unmanned Aerial Vehicles (UAVs) equipped with advanced sensors and combined with Artificial Intelligence (AI) techniques have emerged as a transformative technology for precision agriculture, enabling frequent, high-resolution monitoring of crop health, water status, pest and disease outbreaks, nutrient deficiencies, and yield forecasting.

This Special Issue will focus on the integration of AI and UAV sensor technologies for all aspects of agricultural monitoring, from data acquisition and pre-processing to estimation, prediction, decision support, and actionable farm management insights. Topics of interest include, but are not limited to, multispectral/hyperspectral and thermal sensing, machine and deep learning for feature extraction and anomaly detection, sensor fusion and data quality enhancement, autonomous UAV navigation and mission planning, digital twins in agriculture, and real-world case studies demonstrating the field deployment and impacts of these sensor technologies.

We invite authors to submit original research articles, comprehensive reviews, case studies, and short communications that advance the state of the art in AI-enabled UAV sensing and monitoring for agriculture, with a special emphasis on innovation, practical applicability, and multidisciplinary approaches that bridge sensing technologies with agronomic practices.

Topics of interest for this Special Issue include (but are not limited to) the following:

• AI-based preprocessing and feature extraction from UAV-borne multispectral, hyperspectral, and thermal data;
• Deep learning for crop disease, stress, and phenotyping analysis;
• Sensor fusion, data integration, and spatiotemporal modeling;
• Autonomous UAV systems, path planning, and in-flight decision making;
• Precision irrigation and nutrient management support using predictive models;
• Case studies of real-world deployment in diverse crop systems;
• Explainability and uncertainty estimation in AI for agricultural monitoring;
• Challenges, ethics, and regulatory aspects of UAV-AI integration.

Dr. Jaume Segura-Garcia
Dr. Miguel García-Pineda
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.

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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.