At the critical stage of the global agricultural transformation toward green, intelligence and intensification, building a modern agricultural production system featuring high efficiency, low carbon, resource conservation, ecological friendliness, stability and controllability has become the core goal of modern agricultural development. Relying on multi-source spatial sensing, big data analytics and intelligent management and control technologies, smart agriculture achieves refined management of all factors and the whole process of farmland production. The systematic integration of the agricultural engineering system, research and development of complete sets of equipment, and scenario-based application are the core supports linking basic theoretical research with frontline agricultural production and empowering industrial quality and efficiency improvement. As a low-altitude lightweight intelligent agricultural machinery equipment, agricultural UAVs are characterized by high maneuverability, wide coverage and multi-task adaptability. They integrate multiple functions such as crop remote sensing monitoring, intelligent field operations and emergency disaster disposal, and can adapt to complex agricultural scenarios including plain fields, mountainous and hilly areas, orchards and facility cultivation, covering the whole growth cycle of crops from plowing, sowing, management to harvesting. It has irreplaceable engineering application value in the efficient utilization of cultivated land resources, reduced input of agricultural materials, farmland ecological conservation and clean green production, serving as a core carrier for implementing the concept of agricultural green development and promoting the upgrading of modern agricultural machinery and equipment.

In recent years, the industry has carried out extensive explorations in the optimization of agricultural UAV platforms, visual image processing, intelligent recognition algorithms, flight motion control and other fields, with continuous iteration and upgrading of relevant basic technologies. However, most current studies share common problems of overemphasizing theory over engineering and models over application. A large number of studies are limited to algorithm iteration, model simulation and small-scale experiments in a single environment, lacking systematic adaptability verification in complex and variable field environments, and failing to form a complete engineering technical system covering data collection, feature analysis, law judgment, intelligent decision-making to field operation execution. Meanwhile, insufficient integration of research and design with regional planting patterns, cultivation management specifications and agronomic production demands leads to a prominent disconnection between agricultural machinery and agronomic management systems, which can hardly meet the practical requirements of large-scale and standardized agricultural production. In addition, most field verification tests are short in cycle and limited in coverage, lacking support from multi-year, multi-regional and long-term continuous experimental data. The insufficient technical stability, universality and industrialization promotion value result in the difficulty in the transformation and application of a large number of cutting-edge research achievements, which cannot effectively support the large-scale and systematic development of green agriculture.

To address real engineering problems in agricultural production and strengthen the systematic construction and scenario-based application of the technical system, this special issue takes the green and low-carbon development of agriculture as the main line, and fully highlights the systemic, engineering, practicality and scalability of the research. This special issue gives priority to soliciting original research papers and reviews rooted in production practice, with a complete engineering implementation path, integrated with the concept of collaborative design of agricultural machinery and agronomy, and verified by multi-year continuous positioning experiments or multi-regional and multi-point repeated experiments in a single cycle. Research results with two or more years of long-term in-situ field observation data and multi-regional comparative experiment verification are preferentially accepted, and fragmented research based on single model simulation and small-scale short-term experiments is rejected. Encouragement is given to promoting the in-depth integration and integrated integration of UAV hardware platforms, multi-source sensing payloads, spatiotemporal big data interpretation, intelligent decision-making models, precision operation equipment and regional characteristic agronomic models from the perspective of agricultural systems engineering, and driving the transformation from single technological breakthroughs to complete sets of solutions and large-scale engineering applications.

The main call-for-paper directions of this special issue include but are not limited to:

(1) Precise analysis of crop phenotypes, dynamic monitoring of group growth, global diagnosis of biotic and abiotic stresses based on UAV multi-modal low-altitude remote sensing, and research and development of systematic sensing technologies for large-scale planting.

(2) Fusion and mining of UAV multi-source remote sensing data, combined with dynamic judgment of growth stages, quality evaluation and precise identification of maturity, to build a full-chain decision support system for yield prediction, dynamic optimization of harvest period and field management regulation.

(3) Optimization of UAV precision targeted pesticide application, variable slow-release fertilization, uniform seed sowing and other operation technologies in line with green production requirements, improvement of supporting operation equipment, calibration of working condition parameters and construction of a green operation engineering system.

(4) Analysis of spatial heterogeneity of soil water and fertilizer in farmland, evaluation of vegetation ecological pattern, monitoring of non-point source pollution and dynamic evaluation technology of cultivated land ecological quality based on UAV monitoring means.

(5) Construction of an air-ground integrated collaborative operation system of UAVs, ground intelligent agricultural machinery and fixed sensor monitoring networks, multi-equipment collaborative scheduling, zoning management mode and large-scale field engineering deployment scheme.

(6) Engineering control technologies for UAV autonomous cruise, dynamic obstacle avoidance, adaptive path planning and high-precision stable operation under extreme working conditions such as complex field terrain and meteorological disturbances.

(7) Construction of a regional crop intelligent management decision-making platform based on UAV long-term field monitoring big data, forming reproducible and scalable field production regulation schemes and large-scale application demonstrations.

(8) Research on the integration and adaptation of UAV intelligent equipment with localized cultivation systems, tillage modes and green cultivation technologies, and exploration of a new green agricultural engineering model with in-depth collaboration between agricultural machinery and agronomy.

This special issue aims to build a high-level academic exchange platform for the integration of engineering innovation and production practice of agricultural UAVs, and centrally display high-quality achievements in systematic research and development, long-term experimental verification and multi-scenario adaptive application in this field. It will break the integration barriers between low-altitude intelligent equipment and modern agricultural systems, improve the complete engineering technical system for the application of UAVs in smart agriculture, and provide a solid theoretical basis, complete technical solutions and scalable practical examples for promoting the in-depth integration of agricultural machinery and agronomy, implementing the goals of agricultural fertilizer and pesticide reduction and low-carbon production, and enhancing the overall engineering application level of smart agriculture.

Keywords

Agricultural UAVs; Smart Agriculture; Green and Sustainable Development; Precision Operation; Engineering Application

Guest Editors

(1) Prof. Yong He, Zhejiang University, yhe@zju.edu.cn 

(2) Prof. Manoj Karkee, Cornell University, mk2684@cornell.edu 

(3) Prof. Zhou Yang, South China Agricultural University, yangzhou@scau.edu.cn 

(4) Prof. Xirui Zhang, Hainan University, zhangxr@hainanu.edu.cn 

(5) Prof. Xiongzhe Han, Kangwon National University, hanxiongzhe@kangwon.ac.kr 

(6) Dr. Jie Guo, Hainan University, jie.guo@hainanu.edu.cn 

Timeline

1. For submission to this special issue, please submit a 1–2 page extended English abstract (including title, authors, main content and data) before June 30, 2026. Send the abstract to the journal email ea@cau.edu.cn for review by guest editors. Authors whose abstracts meet the journal and special issue themes will be invited to submit full papers.

2. Full papers must be submitted via the journal system before September 30, 2026.

Submission website: https://mc.manuscriptcentral.com/fase 

Author guidelines: https://journal.hep.com.cn/fase/EN/guidelines 

Journal Introduction

ENGINEERING Agriculture (EA) is an international English journal co-sponsored by the Chinese Academy of Engineering, China Agricultural University and Higher Education Press. The Editor-in-Chief is Fusuo Zhang, member of the Chinese Academy of Engineering and Professor of China Agricultural University, the Executive Editor-in-Chief is Prof. Wei Chen, member of the Chinese Academy of Engineering and President of China Agricultural University.

EA is indexed in major international databases, including DOAJ, Scopus, ESCI, and CSCD. The journal has a 2024 Impact Factor of 2.8 and a five-year Impact Factor of 3.5, ranking in JCR Q1 in Agronomy. Its 2024 CiteScore is 5.6, placing it in Q1 in both the General Agricultural and Biological Sciences category and the General Veterinary category.

EA is a fully open-access journal and does not charge article processing fees. Dedicated to advancing global agricultural modernization through engineering-oriented agricultural science and technology, EA publishes work that explores scientific discovery and technological innovation in agriculture while emphasizing the translation of science and technology into practical engineering solutions that address real-world challenges and drive agricultural transformation and progress.

Journal website: http://journal.hep.com.cn/fase