Applications of Multi-Scale Remote Sensing and Machine Learning to Study Agriculture and Agriculture Water Management
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: 30 March 2026 | Viewed by 623
Special Issue Editors
Interests: agriculture; water cycle; evapotranspiration; grassland resources; remote sensing
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensing analysis and application in agriculture
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Remote sensing plays an important role in achieving sustainable agriculture and water resources. With the development of near-earth remote sensing technology, the agricultural field generates big data that must be transformed into information. Machine learning, as an emerging agricultural data analysis technology, is also widely used in the agricultural field, such as land cover/land use monitoring, crop map monitoring, crop evapotranspiration monitoring, drought monitoring and prediction, crop yield prediction and optimization, crop water productivity monitoring and assessment, etc. It has emerged as a powerful method of analyzing remote sensing data that enables remote real-time monitoring of crop and water management conditions. Moreover, machine learning algorithms provide tools to analyze these vast datasets, revealing patterns and insights that can guide decisions on sustainable agriculture.
In this Special Issue, we invite submissions on recent advances in multi-scale remote sensing and machine learning applied to agriculture and agricultural water management to improve the spatial and temporal versatility of remote sensing data. Submissions of socially significant remote sensing applications for agriculture using machine learning algorithms such as random forests (RFs), deep learning (DL), support vector machines (SVMs), and artificial neural networks (ANNs) are also welcome.
Potential topics may include, but are not limited to, the following:
- Remote sensing methods in agriculture and precision agriculture;
- Machine learning algorithms for accurately monitoring crop maps;
- Machine learning algorithms for predicting and accurately monitoring crop yields;
- Remote sensing methods or machine learning algorithms to monitor crop evapotranspiration in catchment or irrigation areas;
- Remote sensing methods for soil moisture and drought monitoring in catchment or irrigation areas;
- Agricultural water monitoring and assessment in catchment or irrigation areas;
- Big data analytics for drought modeling and prediction;
- Tools and methods for crop health/disease monitoring;
- Applications of the Internet of Things in sustainable agriculture;
- Crop models and decision support systems in smart agriculture;
- Theoretical and empirical data-driven techniques;
- High-fidelity agricultural datasets for supervised and unsupervised deep learning;
- Communication technologies in smart agriculture;
- UAVs/FANET for agricultural applications;
- Tools and methods for quantitative analysis of crop-environment interactions.
Dr. Weiwei Zhu
Dr. Ya’nan Zhou
Dr. Nana Yan
Guest Editors
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
- precision agriculture
- crop monitoring
- evapotranspiration
- drought
- agricultural water management remote sensing methods
- machine learning
- data analysis
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