Advancements in Remote Sensing and UAV Technologies for Water Management in Climate-Smart Agriculture Systems
A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Water and Climate Change".
Deadline for manuscript submissions: 20 December 2025 | Viewed by 85
Special Issue Editors
Interests: climate-smart agriculture; climate change; precision agriculture; water management; soil management; sustainable food production
Interests: climate-smart agriculture; high-resolution climate modeling; climate change adaptation; hydroclimate risk assessment; geospatial and big data analysis
Special Issues, Collections and Topics in MDPI journals
Interests: agricultural irrigation; fluid machinery; CFD; remote sensing; water pumps
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Water is one of the most critical resources in agriculture, and its efficient management is essential for ensuring sustainable crop production, particularly in the face of increasing climate variability. This Special Issue focuses on the application of remote sensing and unmanned aerial vehicle (UAV) technologies for smart and precise water management in climate-smart agricultural systems.
The goal of this issue is to synthesize high-quality research and review articles that highlight innovative solutions for monitoring, assessing, and managing water use in agriculture, supporting the transition toward climate-smart agriculture (CSA). Remote sensing and UAVs enable real-time and spatially detailed insights into soil moisture, plant water stress, evapotranspiration, and irrigation efficiency, and help farmers make informed decisions while conserving resources and improving yields.
We invite contributions that cover topics including, but not limited to, the following:
- Climate-smart water management practices using remote sensing technologies;
- UAV-based monitoring of crop water stress and evapotranspiration;
- Remote sensing techniques for soil moisture and irrigation mapping;
- Integration of UAV data with AI and machine learning for water management;
- Precision irrigation systems informed by remote sensing and UAVs;
- Digital twins and GIS tools for modeling water usage in agriculture.
This Special Issue aims to contribute to the advancement of smart, data-driven water management in agriculture and promote sustainable and climate-resilient farming systems globally.
Dr. Muhammad Awais
Prof. Dr. Xander Wang
Prof. Dr. Wei Li
Dr. Selvarajah Thuseethan
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. Water 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 2600 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
- remote sensing
- climate-smart agriculture
- water management
- digital twins
- sustainable farming
- agricultural water use efficiency
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