Environmental Monitoring and Analysis: Latest Advances and Prospects
A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Environmental Sciences".
Deadline for manuscript submissions: 20 February 2026 | Viewed by 58
Special Issue Editors
Interests: real-time prediction systems in support of emergency management; parallel computing in distributed environments; water emergency management; machine learning; reliable monitoring in environmental sensor networks; detection and correction of abnormal measurements in environmental data; automated quality control for aquatic monitoring systems
Special Issues, Collections and Topics in MDPI journals
Interests: numerical modeling applied to estuarine and coastal dynamics; oil spill transport and weathering modeling in oceans, coastal zones, and estuaries; remote sensing for coastal zones and estuaries monitoring, applied to the detection of internal waves, oil spills, bathymetry estimation, water bodies, and coastline evolution
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The way we monitor, quantify, and comprehend environmental systems—from small-scale sensor installations to massive digital twins—has rapidly changed in recent years, with a greater emphasis now being placed on data, intelligence, and communication. And yet, as sensing technologies develop, new challenges arise in terms of processing heterogeneous data, ensuring data reliability, and turning unprocessed observations into insightful knowledge.
Submissions to this Special Issue of Applied Sciences on innovative methods for environmental monitoring and analysis are warmly encouraged. Research showcasing novel sensor networks, real-time data collection systems, or resilient processing pipelines is also welcome, particularly if it tackles issues pertaining to data quality, resilience, and unpredictability. The range of admissible applications includes risk assessment, coastal monitoring, hydrology, and air quality.
We especially welcome submissions with a focus on interdisciplinary integration that integrate environmental science with informatics, artificial intelligence, and system engineering. Our goal is to draw attention to studies that challenge our understanding of and ability to adapt to environmental variability, whether through sophisticated modeling, machine learning, or real-world field applications.
In this quickly changing field, we hope that this collection will be used as a reference for current trends and future developments.
Dr. Goncalo Jesus
Dr. Alberto Carlos Azevedo
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. Applied Sciences 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 2400 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
- environmental monitoring systems
- data quality and uncertainty
- smart sensing and real-time observation
- AI and machine learning in environmental analysis
- digital twins and decision support
- sensor networks and interoperability
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