Dear Colleagues,

“Computer Vision in Precision Agriculture” aims to improve agricultural production efficiency and crop management through the utilization of image processing and machine learning techniques.

This is a data-driven agricultural management approach that aims to optimize agricultural production by accurately monitoring and responding to the needs of crops.

Traditional agricultural management methods often rely on experience and manual observation, which can lead to resource waste and inefficient decision-making. However, computer vision technology can provide more accurate and real-time agricultural information in an automated and intelligent manner, helping farmers and agricultural professionals make wiser decisions. By utilizing images captured by drones, satellites, or ground cameras, valuable information about crops and their health can be extracted. This includes identifying and monitoring crop growth, detecting pests and diseases, assessing nutrient deficiencies, and estimating yield potential. Through the use of computer vision algorithms, farmers and agronomists can make data-driven decisions, optimize resource allocation, improve crop management practices, and enhance overall agricultural productivity.

Our community is highly interested in conducting research related to the intersection of computer vision and precision agriculture. This type of research can encompass various aspects, including but not limited to crop or pest analysis, soil analysis, and operational planning, all aimed at promoting the application and advancement of computer vision technology in the field of precision agriculture. We welcome research articles and reviews in related areas to drive technological innovation in agricultural production efficiency and crop management, while providing intelligent decision support for farmers and agricultural professionals.

We look forward to receiving your contributions.

Dr. Mian Zhou

Section Editor