Sustainable Environmental Science: Application of Machine Learning and Artificial Intelligence in Earth Systems
A Special Issue of Sustainability (ISSN 2071-1050) belonging to the section "Environmental Sustainability and Applications".
Deadline for manuscript submissions: 15 February 2027 | Viewed by 460
Editors
Interests: geostatistics; natural resources evaluation; spatiotemporal predictions; simulations; uncertainty quantification; applied AI; remote sensing; time series analysis; data analysis
Special Issues, Collections and Topics in MDPI journals
Interests: remote sensors; ML methods; geostatistics; satellite imagery; satellite data analysis; space–time (4D) predictive modelling; variograms; simulation methods; applied artificial intelligence; knowledge engineering; wireless network and web servers performance
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
We are pleased to invite submissions to the Special Issue “Sustainable Environmental Science: Application of Machine Learning and Artificial Intelligence in Earth Systems”. Addressing sustainability challenges requires models that capture interactions across climate, water, land, ecosystems, and human activity, and that translate complex evidence into decisions. Alongside rapid advances in Earth observation (satellites, drones, and in situ monitoring) and Earth-system simulations, ML/AI can fuse heterogeneous observations and model outputs, improve predictive skill for extremes, and provide uncertainty-aware products for monitoring, attribution, and scenario assessment.
This Special Issue aims to advance ML/AI through impactful applications in Earth systems that generate actionable insights for sustainability outcomes. We welcome contributions that connect algorithmic innovation to improved environmental understanding, forecasting and early warning, ecosystem and land-surface monitoring, exposure and risk mapping, and sustainable natural-resources management, including evaluation of mitigation and adaptation options. Interdisciplinary submissions are encouraged, including work that couples ML/AI with process understanding, leverages remote sensing and spatiotemporal analytics, and emphasizes robust validation, interpretability, and uncertainty quantification. The goal is to highlight advances that translate into measurable sustainability outcomes, from reduced risk and exposure to improved planning, policy monitoring, and operational decision support.
In this Special Issue, original research articles and reviews are welcome. Topics may include, but are not limited to:
- Renewable-energy resource assessment and sustainable operations using ML/AI.
- Sustainable natural-resource management using ML/AI for planning, monitoring, and optimization.
- Geochemistry and Earth-surface processes modeled with ML/AI.
- ML/AI-based climate and extreme-event forecasting and hazard early warning.
- ML/AI applications in hydrology, drought, floods, water quality, and sanitation analytics.
- Ecosystem and biodiversity indicators derived using ML/AI.
- Air pollution mapping, exposure, and mitigation assessment enabled by ML/AI.
- ML/AI-driven land-use change, desertification, urbanization, and heat-risk modeling.
- Physics-informed and hybrid ML models, uncertainty quantification, and interpretability.
- Applications of neural-network families (ANN/DNN, CNN/U-Net, PINNs, etc.) for Earth systems.
- Open data, benchmarks, and reproducible ML/AI workflows for Earth systems.
- Applications of generative AI and diffusion models for spatiotemporal synthesis, data augmentation, and scenario generation.
I look forward to receiving your contributions.
Dr. Andrew Pavlides
Dr. Anna Kamińska-Chuchmała
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 250 words) can be sent to the Editorial Office for assessment.
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-anonymized peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Sustainability 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
- machine learning
- artificial intelligence
- earth systems
- sustainable natural-resources management
- renewable energy management
- uncertainty quantification
- remote sensing
- sustainability
- neural-networks
- environmental monitoring and forecasting
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