Novel Applications of UAV and Image Processing for Agriculture
A special issue of Agriculture (ISSN 2077-0472). This special issue belongs to the section "Digital Agriculture".
Deadline for manuscript submissions: 10 June 2024 | Viewed by 934
Special Issue Editor
Special Issue Information
Dear Colleagues,
With the continuously growing global population, the agricultural industry is facing tremendous pressure to increase crops’ yield and quality to meet the growing demand for food. At the same time, reducing the adverse environmental impact of agricultural activities has become an urgent task. In this context, unmanned aerial vehicle (UAV) imaging technology has introduced new solutions to the agricultural sector by providing high-resolution aerial images and data. Equipped with advanced imaging sensors, UAVs can capture subtle the changes in and features of plants, providing a detailed understanding of crop health. These sensors can measure indicators such as the chlorophyll content, leaf area index, and plant height, helping farmers and researchers monitor the crop growth conditions and potential issues. With UAV imaging technology, they can quickly detect crop pests, nutrient deficiencies, water stress, and take appropriate measures for management.
Furthermore, UAV imaging technology can also be used for crop biomass estimation and yield prediction. By collecting a large amount of UAV image data and combining image processing algorithms and machine learning techniques, researchers can establish accurate models to estimate the crop biomass and predict the yield. This provides crucial decision support for farmers, helping them optimize agricultural management and resource allocation, thereby improving the production efficiency and economic benefits.
In the current agricultural industry, which must meet the growing demand for high-quality agricultural products and reduce the environmental impact, UAV imaging technology has become a powerful tool in modern agriculture. The utilization of advanced imaging sensors and image processing algorithms is particularly important, with a specific focus on crop health, biomass estimation, yield prediction, and pest and disease forecasting.
Dr. Tao Liu
Guest Editor
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Keywords
- UAV (unmanned aerial vehicle)
- advanced imaging sensors
- image processing algorithms
- crop health
- biomass estimation
- yield prediction
- pest and disease forecasting
