Special Issue "Artificial Intelligence Applications in Remotely Sensed Hydrologic and Water Systems"
Deadline for manuscript submissions: closed (15 June 2023) | Viewed by 3235
Interests: image processing; environmental data analysis; hyperspectral imaging; object-based image analysis
Interests: urban hydrology; flood risk assessment; hydroinformatics; data-driven modelling; uncertainty analysis; stormwater management
Special Issues, Collections and Topics in MDPI journals
Interests: satellite imagery; rain radar; artificial intenlligenc; biometeorology; hydrometerology; argometerology
As natural and built systems are undergoing major challenges due to the impact of climate change and rapid urban development, new analytics and modeling solutions are required to study such spatiotemporal systems under dynamic conditions and modeling objectives. This also involves the utilization of diverse and large sources of information, amounting to massive databases or new sources of intelligence. Recent advances in artificial intelligence and computational resources facilitate innovative data-driven modeling approaches which can accommodate the changing nature of hydrological systems. The addition of remote sensing techniques enables the use of massive databases and real-time monitoring of hydrologic phenomena.
Remote Sensing is launching a special issue entitled “Artificial Intelligence Applications in Remotely Sensed Hydrologic and Water Systems.” This issue aims to promote state-of-the-art data-driven and machine learning techniques such as deep learning, ensemble learning, and reinforcement learning, using remote sensing in water research spanning hydro-climatology, hydroinformatics, and hydro-meteorology. Applications of interest include, but not limited to, hazard monitoring, forecasting of extreme events, pollution analysis, mapping of renewables, surface water systems, sociotechnical analysis, hydroinformatics, environment and sustainable agriculture applications. Research featuring advances in statistical modeling approaches is also invited. Consideration will be also given to interdisciplinary methodologies in uncertainty analysis, state-estimation, model interpretability, system identification and relational mapping of remotely sensed systems.
Dr. Prashanth Reddy Marpu
Dr. Usman T. Khan
Dr. Ju-Young Shin
Dr. Mohammad H. Alobaidi
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.
- machine learning
- big data analytics
- data assimilation
- spatiotemporal modeling