Innovative Technologies and Remote Sensing Methodologies for Irrigation Scheduling in Vegetable, Fruit and Ornamental Crops
A special issue of Horticulturae (ISSN 2311-7524).
Deadline for manuscript submissions: closed (20 June 2023) | Viewed by 605
Special Issue Editors
Interests: plant water relations; irrigation research; plant-based sensor systems; climate impact research
Special Issue Information
Dear Colleagues,
Efficient irrigation management is key for sustainable horticulture, and its importance increases because of climate change and the limited resources available. Monitoring crop water requirements using proxy and remote sensing methods is probably the most focused-on research field in irrigation and water management. Non-contact and real-time detection of crops’ supply status combined with digitized and automatable crop management offers high potential for practical application. Innovative technologies that feature high usability, efficiency, and accuracy may fulfill the needs of appropriate irrigation management in high-value crops. This Special Issue will comprise a collection of papers to present and evaluate current knowledge and methods of irrigation scheduling using models and algorithms of UAV-based spectral, hyperspectral, thermal, and satellite imaging. This includes image processing, novel sensing technologies integrated in irrigation management, crop water stress indicators, artificial intelligence, and machine learning applications. Multi-platform and irrigation management systems may also be covered. The scientific approaches must satisfy the requirements of practical applicability in equal measure in terms of data availability and automatable processing. This Special Issue will contribute to the exchange of opinions, discussions, and solutions to enhanced irrigation management in irrigated horticulture, particularly of vegetable, fruit, and ornamental crops, via remote sensing technologies that address underexplored practical challenges through our forum and the publication of your research. We wish to promote the exchange of mature and new approaches between different countries.
Prof. Dr. Jana Zinkernagel
Dr. Angeliki Elvanidi
Guest Editors
Manuscript Submission Information
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Keywords
- satellite imagery
- ground-based imagery
- image processing
- spectral and hyperspectral data
- crop water stress indicator
- machine learning
- precision horticulture
- irrigation management
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