Root-Zone Soil Moisture Retrieval and Applications from Remote Sensing Measurements
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Environmental Remote Sensing".
Deadline for manuscript submissions: 31 August 2025 | Viewed by 3800
Special Issue Editors
Interests: data assimilation; NWP; soil moisture; machine learning
Interests: data assimilation; soil moisture; vegetation; fluxes; machine learning
Interests: soil moisture; flood; drought; irrigation; remote sensing
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Satellite-derived SM measurements are mainly confined to a thin surface layer with a depth of a few centimetres. However, the root-zone SM, with a depth of up to 3 metres, is a significant driver of latent and sensible heat fluxes, vegetation phenology, and the water cycle. Fortunately, root-zone SM is connected to variables that can be detected by satellites, including surface SM, vegetation optical depth, solar-induced fluorescence, and ground water storage, amongst others.
Over the last few decades, land surface data assimilation systems have become established at various institutes, including NWP centres and universities. Both active (e.g., Metop-ASCAT) and passive (e.g., SMOS, SMAP) satellite-derived SM observations can be assimilated in land surface models. Furthermore, observed vegetation and agriculture from satellites have a strong relationship with root-zone SM, especially during the growing season. Traditionally, radiative transfer observation operators transform the SM model state to the observed quantity (e.g., brightness temperature for SMOS/SMAP) prior to assimilation. More recently, efficient machine learning-based observation operators have been advocated, including neural networks and gradient boosting trees.
This Special Issue aims to collect studies on innovative methods to derive root-zone SM using remote sensing measurements and applications of root-zone SM derived from remote sensing.
Themes include but are not limited to the following:
- Data assimilation;
- Machine learning;
- Drought monitoring;
- Flood monitoring;
- Agriculture monitoring;
- Irrigation;
- SM validation;
- NWP.
Both research and review articles are relevant.
Dr. David Fairbairn
Dr. Bertrand Bonan
Dr. Luca Brocca
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
- root-zone
- soil moisture
- data assimilation
- machine learning
- remote sensing
- observations
- vegetation
Benefits of Publishing in a Special Issue
- Ease of navigation: Grouping papers by topic helps scholars navigate broad scope journals more efficiently.
- Greater discoverability: Special Issues support the reach and impact of scientific research. Articles in Special Issues are more discoverable and cited more frequently.
- Expansion of research network: Special Issues facilitate connections among authors, fostering scientific collaborations.
- External promotion: Articles in Special Issues are often promoted through the journal's social media, increasing their visibility.
- Reprint: MDPI Books provides the opportunity to republish successful Special Issues in book format, both online and in print.
Further information on MDPI's Special Issue policies can be found here.
