Assessment of Methane Emission from Rice Paddies and Water Management Using Remote Sensing Technology
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Engineering Remote Sensing".
Deadline for manuscript submissions: 30 November 2025 | Viewed by 228
Special Issue Editors
Interests: image data analysis; SAR data analysis; agricultural research
Interests: remote sensing; forest; agriculture; carbon cycle
Interests: earth observation satellite remote sensing; geoinformatics; environmental monitoring; spatio-temporal image processing; agriculture; public health
Interests: remote sensing of disasters and environment; wetland ecosystems; blue/green/black/brown carbon studies; socio-economic impact assessment with night-time light; flood/drought and cropland monitoring; global air pollutant emission inventory study
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Methane is one of the most important greenhouse gases causing climate change, and there are significant methane emissions from paddy fields in Asia and other regions. Recently, the water management method, called Alternate Wetting and Drying (AWD), has been drawing attention due to its potential to save fresh water resources and to reduce methane emissions. Furthermore, the amount that methane emissions are reduced can be used in carbon trading and provide money to farmers, but the Measurement, Reporting and Verification (MRV) systems used to account for and value the methane emission reduction efforts of farmers using AWD methods and to generate carbon credits saleable on the market can be costly and time-consuming. Therefore, recently, there have been many studies assessing methane emissions from rice paddy fields and water management using remote sensing as a complemental MRV system in a cost- and time-effective way.
Within this context, this Special Issue aims to present articles that focus primarily on assessing methane emissions from rice paddy fields and water management using remote sensing and AI/ML. The Special Issue welcomes articles concerning novel approaches or case studies in the study of remote sensing. Topics can be related, but not limited, to the following:
- Water level change detection in paddy fields using remote sensing technology;
- Polarimetric SAR change detection of water level;
- Hyperspectral or MSS remote sensing change detection of water level and rice crop growth or biomass;
- Adversarial and/or IOT learning with field survey for change detection of water level or rice crop growth or biomass;
- Explainable AI for change detection of water level with GHG emission assessment.
Dr. Shinichi Sobue
Dr. Thuy Le Toan
Dr. Kei Oyoshi
Prof. Dr. Wataru Takeuchi
Guest Editors
Manuscript Submission Information
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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.
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Keywords
- methane emission
- water level
- water management
- polarimetric SAR change detection
- remote sensing
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