Multi-Sensor Remote Sensing for Soil Moisture Monitoring
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 28 February 2026
Special Issue Editors
Interests: environment of remote sensing; land use change and effect
Special Issues, Collections and Topics in MDPI journals
Interests: Remote Sensing; Machine Learning
Interests: complexity theory of spatial network; application of quantitative remote sensing in forestry; carbon use efficiency of forest ecosystem
Special Issues, Collections and Topics in MDPI journals
Interests: hydrology; environmental hydrology; hydrological modeling; hydrometry; WRM; irrigation; irrigation water management; soil hydrology; geographical information systems (GIS)
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Acting as a vital participant in the Earth's "breathing" process, soil moisture is a key component in the Earth system, playing a central role in land–atmosphere interactions, hydrological processes, vegetation dynamics, and climate feedbacks.
Earth observation technologies have rapidly advanced, greatly improving our ability to retrieve soil moisture across varied spatial and temporal scales. While passive and active microwave sensors remain key tools for large-scale soil moisture monitoring, their limitations in spatial resolution and vegetation penetration have highlighted the value of multi-sensor integration. Combining microwave data with optical, thermal, hyperspectral, and LiDAR observations has enhanced soil moisture inversion through data fusion, machine learning, and physically based models. Recent progress in satellite constellations, UAV-based platforms, in situ networks, and modeling techniques offers unprecedented opportunities for more accurate and scalable soil moisture mapping.
This Special Issue will bring together contributions focusing on the development, validation, and application of soil moisture inversion models using multi-sensor Earth observations. We encourage studies that explore the synergistic use of different data modalities, multiscale data fusion strategies, and innovations in inversion modeling frameworks. Particular emphasis is placed on studies addressing soil moisture inversion based on multi-sensor remote sensing data, especially those involving field-based validation, hybrid modeling strategies combining physical and data-driven approaches, and the practical application of inversion outputs in agroecological systems or environmental monitoring contexts. Articles may address, but are not limited, to the following topics:
- Soil moisture retrieval from multi-sensor data;
- Machine learning and deep learning models for soil moisture inversion;
- UAV-based sensing and fine-scale soil moisture mapping;
- Soil moisture dynamics and its role in drought/flood monitoring;
- Uncertainty analysis and validation of soil moisture inversion using in situ observations and ground truth data;
- Multi-sensor data fusion strategies for spatiotemporal enhancement of soil moisture products.
Prof. Dr. Jiang Qun’ou
Dr. Yu Qiang
Dr. Chen Na
Dr. Konstantinos X. Soulis
Guest Editors
Dr. Qunou Jiang
Dr. Na Chen
Dr. Qiang Yu
Dr. Konstantinos X. Soulis
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
- • Soil moisture inversion
- • Multi-sensor remote sensing
- • Machine learning
- • UAV-based observation
- • Data assimilation
- • Hydrological modeling.
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