Remote Sensing for Enhanced Agricultural Crop Management

Dear Colleagues,

Continuous advances in monitoring technologies, and particularly in remote sensing, have spurred a great revolution in agricultural activity. Remote sensing has become a key tool in modern agriculture, enabling the non-invasive, affordable, and high-frequency monitoring of crop conditions, soil properties, and environmental factors. Through the use of spectral data and vegetation indices, remote sensing facilitates the early detection of biotic and abiotic stress, the assessment of biomass, yield estimation, and the optimization of inputs such as water and fertilizers, among others. Of the available platforms, satellite-based remote sensing tools enable wide coverage and historical data series. In contrast, unmanned aerial vehicles (UAVs or drones) provide high-resolution, on-demand imagery, and great flexibility in terms of flight planning, making them especially suited for plot-level analysis and precision agriculture interventions. UAVs can be equipped with RGB, multispectral, thermal, or LiDAR sensors to support tasks ranging from disease detection to canopy structure modelling. The combination of both satellite and drone-based data within proximal sensing monitoring systems represents a promising path to robust, multi-scale agricultural decision support tools. The aim of this Special Issue is to showcase recent advances in the development and application of remote sensing technologies and tools, from satellite platforms to UAV-based systems, for improving crop monitoring, resource management, and decision-making in agricultural systems under current and future challenges.

The scope of this Special Issue covers a broad range of topics, including various remote sensing platforms and monitoring sensors, as well as their applications across multiple crop types. We encourage the submission of original research articles, reviews, and perspectives that present and analyze innovative approaches to improving agricultural management. Research areas may include, but are not limited to, the following:

• Innovative applications of remote sensing for agricultural monitoring and management.
• The application of remote sensing in precision farming.
• Comparative assessments of satellite and UAV data for agricultural decision-making.
• Multitemporal analysis for change detection in agricultural areas.
• The evaluation of image processing techniques for the identification of biotic and abiotic stress.
• The use of remote sensing data combined with artificial intelligence for decision-making or automatic classification in precision agriculture.
• Point cloud-based solutions for fruit tree management.
• The integration of remote sensing with proximal sensing tools for enhanced agronomic GIS.

Dr. Pedro V. Mauri
Dr. Lorena Parra
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. 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 1600 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.

• Precision farming
• agronomy
• drone
• satellite
• unmanned aerial vehicle
• stress
• yield