Soil Moisture Observation Using Remote Sensing and Artificial Intelligence
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "AI Remote Sensing".
Deadline for manuscript submissions: closed (30 September 2024) | Viewed by 491
Special Issue Editors
Interests: soil water model; remote sensing; intelligent agriculture; artificial intelligence
2. Department of Civil Engineering, Monash University, Clayton, Australia
Interests: remote sensing; radar; water resource; intelligent agriculture; artificial intelligence
Special Issues, Collections and Topics in MDPI journals
Interests: polarimetric synthetic aperture radar; active and passive microwave; soil moisture; crop biophysical parameter
Interests: soil and water pollution; water supply; green infrastructures; remote sensing; machine learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Soil moisture (SM) is a key state variable that plays an important role in linking energy and carbon cycles, as well as terrestrial water in various hydrological and meteorological applications. The impact of SM in evapotranspiration, photosynthesis, runoff, soil respiration, flood events, surface heat flux partitioning, and droughts is very prominent. SM has a direct impact on soil dryness and can indirectly influence the atmospheric vapor pressure deficit. Thus, the seasonal variability of SM is a key element for land capacity to act as a carbon sink. The systematic monitoring of SM trends around the globe is vital for a better understanding of future climate change situations. Remotely sensed data offers the derivation of SM data on a global scale. Additionally, remotely sensed data for SM has advanced enormously in recent years. Artificial intelligence (AI) techniques have been integral in every field, including the processing of remote sensing (RS) data. AI achieves high performance, high accuracy, and is correlated with low statistical errors as a rapid decision tool under changing climate conditions.
This Special Issue aims to showcase studies covering different applications of different AI techniques on different types of remote sensing data from a variety of sensors for soil moisture. This Special Issue may aid in soil moisture for agriculture, the relationship between climate and soil moisture, soil moisture from different sensors with different levels of spatial and temporal resolution, and more comprehensive aims and scales. Multiscale studies and studies related to ecosystem services are welcome. Articles may address, but are not limited to, the following topic:
- Soil characteristics using remote sensing and artificial intelligence;
- Soil moisture mapping using remote sensing;
- Satellite-based soil moisture estimation, calibration, and evaluation;
- Soil moisture product downscaling;
- The gap filling of remotely sensed soil moisture products;
- Soil moisture data assimilation into hydrological models;
- The relationship between climate change and soil moisture using artificial intelligence
- Spatio-temporal trends for soil moisture using remote sensing data and artificial intelligence techniques;
- The use of remote sensing data for soil moisture in precision agriculture.
We hope you will contribute your high-quality research, and we look forward to reading your valuable results.
Dr. Yuanyuan Zha
Dr. Liujun Zhu
Dr. Hongtao Shi
Dr. Ignacio Melendez-Pastor
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
- artificial intelligence
- model performance
- soil moisture
- sustainability
- evapotranspiration
- remote sensing
- SMAP
- data assimilation
- downscaling
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.
- e-Book format: Special Issues with more than 10 articles can be published as dedicated e-books, ensuring wide and rapid dissemination.
Further information on MDPI's Special Issue polices can be found here.
