Remote Sensing Applications for Pest Detection in Agriculture
A special issue of AgriEngineering (ISSN 2624-7402).
Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 3098
Special Issue Editor
Interests: machine vision and machine learning for plant phenotyping and precision agriculture; plant nutrient estimation; plant disease detection; drought and salt stress tolerance; plant growing status estimation; invertebrate pest detection
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Pests, including weeds and invertebrate pests, are the major source of crop yield loss worldwide. Weeds compete with crops for nutrients and water. Invertebrate pests, such as locusts, aphids and snails, consume corps and spread disease. Effective control of pest is critical for maximising crop yields and meeting quality standards at harvest. However, currently, the agricultural industry is highly reliant on “broad-spectrum” pesticides to control pests. As a result, the overuse of pesticides has resulted in pests developing resistance to pesticides. It also pollutes our environment and threatens food safety. In precision agriculture, if the location, time, species and populations of pests in the fields were available, instead of heavily relying upon pesticide, site specific weed management (SSWM) or integrated pest management (IPM) would use the optimized combination of mechanical, chemical, biological and genetic tools to control pests. Therefore, pest detection is a prerequisite of SSWM and IPM.
This Special Issue aims to provide researchers with a platform to share the state-of-art remote sensing applications for pest detection in agriculture. With this special issue, we invite you to share your high-quality research results and put new insights into pest detection technologies. Original research papers or review papers are welcome. Contributions are expected to deal with, but are not limited to the following areas:
- Sensors and Instrumentation
- Hyperspectral or multispectral sensing
- Machine vision or computer vision
- Robotics
- Automation
- Artificial intelligence
- Satellite imaging
- Unmanned aerial vehicle applications
- Ground-base platform
- Greenhouse applications
Dr. Huajian Liu
Guest Editor
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
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 quarterly 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.
Keywords
- invertebrate pest detection
- weed detection
- remoting sensing
- site specific weed management
- integrated pest management
- precision agriculture
