Multi-Source Remote Sensing for Agricultural Water and Soil 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: 20 June 2026 | Viewed by 88
Special Issue Editors
Interests: farmland soi; crop moisture estimation; multi-source remote sensing information fusion
Interests: multi-source remote sensing data fusion algorithm and application; crop classification and yield estimation; surface evapotranspiration and crop drought monitoring
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Water and soil are the foundational cornerstones of agricultural ecosystems. As a key driver, water directly constrains crop yield and affects resource use efficiency, while soil serves as the bedrock for maintaining food security and ecosystem functions. Against the backdrop of accelerating global climate change and increasing anthropogenic pressures, the challenge of rapidly and reliably capturing the spatiotemporal dynamics of key water–soil parameters has emerged as a critical issue that must be resolved to achieve precision agriculture and sustainable agricultural development. Fortunately, multi-source remote sensing technologies, ranging from satellites to unmanned aerial vehicles, provide unprecedented cross-scale observational capabilities to address this challenge.
This Special Issue is dedicated to the theme of "Multi-Source Remote Sensing for Monitoring Farmland Water Status and Quantitative Soil Property Research," which aligns perfectly with the journal's commitment to advancing environmental remote sensing, precision agriculture, and sustainable development. The Issue will focus on cutting-edge methodologies that leverage multi-source remote sensing data—including optical, thermal infrared, radar, and LiDAR—for synergistic retrieval and integrated analysis. These approaches aim to accurately quantify key traits such as crop water stress, soil moisture, organic matter, salinity, and physical structure, thereby providing essential data and theoretical support for understanding and optimizing agricultural ecosystems.
For this Special Issue, we cordially invite academic colleagues to submit four types of manuscripts: original research, review articles, technical notes, and communications. Suggested topics include, but are not limited to, the following:
- Applications of multi-sensor data fusion technology in retrieving farmland water–soil parameters;
- Novel retrieval algorithms integrating physical mechanisms with machine learning;
- Quantitative remote sensing monitoring of crop water stress, evapotranspiration, and soil properties (e.g., organic carbon, compaction);
- Rigorous ground validation and uncertainty analysis of remote sensing products;
- Explicit physical interpretation linking remote sensing signals with agro-hydrological and soil processes;
- Multi-scale agricultural water resource management and soil health assessment based on remote sensing;
- Innovation and application of machine learning and deep learning algorithms.
Dr. Caixia Li
Prof. Dr. Liang Sun
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 250 words) can be sent to the Editorial Office for assessment.
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
- multi-source remote sensing
- soil moisture
- evapotranspiration
- data fusion
- machine learning
- deep learning
- precision agriculture
- soil and crop health
- agricultural field management
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