Advanced Machine Learning and Remote Sensing in Agriculture
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Agriculture and Vegetation".
Deadline for manuscript submissions: closed (1 March 2022) | Viewed by 22228
Special Issue Editor
Interests: machine learning; computer vision; image processing; pattern recognition; remote sensing; application in agriculture
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing has a pivotal role in many areas of research and applications. Indeed, the last decade has seen significant technological advances in sensors, data acquisition, storage, and computing resources. The availability of data at multiple scales over large geographical areas has great potential to enable interesting methodologies and knowledge development in the agricultural domain. On the other hand, advanced machine learning has emerged as a powerful approach for analyzing remote sensing data. There is a growing trend to develop such an approach to assist in the digital transformation of agriculture, such as land use monitoring, crop yield forecasting and optimization, ecosystem management, etc.
However, despite these advances and the growing level of knowledge, significant challenges remain in the processing and analysis of remote sensing images in agriculture. For instance, the semantic gap between the information contained in the images and the functioning of crops or biophysical models, unlabeled and unbalanced data, generalization of learned models across different scales and environments, model explicability and interpretation, etc.
This Special Issue will disseminate the latest research findings in the machine learning methods using remote sensing data. It includes but is not limited to crops classification, disease identification and assessment, yield prediction and optimization, phenotyping, etc.
Dr. Adel Hafiane
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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
- Supervised and unsupervised learning
- Weakly learning
- Deep learning
- Domain knowledge and adaptive learning
- Semantic models
- Generative models
- Feature engineering
- Crop monitoring and tools
- Ecosystem and environment management
- Agricultural models
