Remote Sensing, Sensor Fusion, and Artificial Intelligence for Sustainable Agriculture

Dear Colleagues,

This Special Issue calls for translational research that applies innovative remote sensing technologies to solve critical challenges and enhance the sustainability, resilience, and efficiency of modern agricultural systems. The goal is to bridge the gap between technological innovation and practical application, fostering solutions with direct relevance to global food security and environmental stewardship. We invite submissions of original research articles and comprehensive reviews that advance innovations beyond methodological demonstration to address tangible, real-world agricultural problems—work that cuts across relevant fields and disciplines is especially welcome. Contributions are expected to provide novel mechanistic insights, evaluate environmental implications, or discuss the policy frameworks needed for broader adoption.

Areas of interest for this Special Issue include, but are not limited to, the following topics:

• Crop mapping, classification, and health monitoring;
• Soil property mapping and health assessment;
• Remote sensing platforms and sensor fusion (satellite, UAV, and IoT);
• Artificial intelligence (AI), machine learning (ML), and deep learning (DL) applications for agricultural analytics;
• Remote sensing for food security and early warning systems;
• Tracking agricultural land use dynamics (expansion, abandonment, and intensification);
• Assessing carbon sequestration, monitoring greenhouse gas emissions, and evaluating climate adaptation/mitigation practices;
• Assessing the impacts of climate change and extreme events on agricultural productivity and sustainability;
• Remote sensing applications for controlled environment agriculture;
• Explainable AI (XAI) in agricultural remote sensing.

This Special Issue will address a critical translational gap in the agricultural remote sensing literature. While extensive research demonstrates the technical capabilities of novel sensors and algorithms, much of this work remains confined to methodological validation. A persistent disconnect exists between technological innovation and the adoption of scalable, decision-ready solutions in complex, real-world farming systems. We seek contributions that translate technological advancements into actionable insights for stakeholders, thereby demonstrating performance under operational constraints. Furthermore, this Special Issue seeks to integrate currently fragmented scholarly discussions; therefore, we welcome interdisciplinary work that connects, for example, AI-/ML-driven remote sensing with soil science, climate mitigation, and policy analysis. By fostering submissions on explainable AI and sensor fusion for novel agronomic insights, the we hope to create vital cross-disciplinary linkages and advance holistic agricultural assessment tools.

Dr. Rasha M. Abou Samra
Guest Editor

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-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. AgriEngineering is an international peer-reviewed open access monthly 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 1800 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.

• remote sensing
• precision agriculture
• sustainable agriculture
• food security
• crop monitoring
• multi-/hyperspectral imaging
• artificial intelligence/machine learning
• sensor fusion
• land use/land cover change
• yield prediction
• climate-smart agriculture