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SOAP4Earth: 1st Invited Session on Smart Observation And Preservation for Earth
The session will be held in Osaka, Japan (in-person and virtual)
10th - 12th September 2025
in conjunction with the 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025)
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AIMS AND SCOPE:
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The rapid advancements in Artificial Intelligence (AI) and remote sensing technologies have significantly transformed how we observe and protect the planet. Earth Observation (EO) instruments—including multispectral and hyperspectral satellites, radar systems, LiDAR sensors, and ground-based monitoring devices like meteorological stations and seismic sensors—are generating vast amounts of data.

Recent machine learning and deep learning models enable researchers to process and analyze these high-dimensional datasets with exceptional precision. These techniques enhance the detection of complex spatio-temporal patterns, subtle anomalies, and emerging trends, surpassing conventional analytical methods.

The synergy between AI and remote sensing plays a crucial role in addressing global challenges such as climate change and disaster management. AI-driven EO data analysis allows for early detection of environmental anomalies, supporting climate mitigation and adaptation strategies. Additionally, real-time monitoring helps manage natural disasters like floods, wildfires, and earthquakes, enhancing risk reduction and community protection. AI-powered remote sensing also contributes to predictive maintenance and fault detection in critical infrastructure.

Emerging methodologies in this field include deep learning-based feature extraction, domain adaptation, semi-supervised learning, time series analysis, active learning, explainable AI, and uncertainty quantification. However, a major challenge remains in bridging the gap between domain experts and AI researchers to improve the interpretability and applicability of AI-driven EO systems.


TOPICS:
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The topics of interest include (but are not limited to), the areas listed below:
- Satellite image analysis for environmental monitoring and disaster management
- Modelling and simulation of natural phenomena
- Geospatial data fusion, analytics, and knowledge discovery in Earth Observation
- Explainable and trustworthy AI in climate and Earth Sciences
- Cyber-Physical systems and IoT for real-time Earth Observation
- Edge and On-Board computing for scalable Earth Observation
- Digital traceability and transparent environmental governance
- AI-Driven solutions for sustainable development goals


PAPER SUBMISSION:
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Submitted papers (up to 10 pages including references) will be reviewed by three members of Program Committee (or their sub-reviewers) and selection of accepted papers will be based on relevance, quality and originality. Ensuring the reproducibility of the results is a highly appreciated feature of the contributions.
Accepted papers will be published in a Elsevier's Procedia Computer Science open access journal (https://www.sciencedirect.com/journal/procedia-computer-science/about/aims-and-scope). At least one of the (co)author(s) of each accepted paper is required to register and attend the conference to present the work.

Authors must use the Procedia templates obtainable at: http://kes2025.kesinternational.org/submission.php.
All papers for the SOAP4Earth Session should be submitted via dedicated EasyChair (link on website).

If you have any questions regarding the submission of manuscripts, please contact one of the Session Chairs.


VENUE:
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The conference will be held in Osaka, Japan.
More info will be available soon on the 29th International Conference on Knowledge-Based and Intelligent Information & Engineering Systems (KES 2025) (http://kes2025.kesinternational.org/)


SESSION CHAIRS:
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- Stefano Marrone, Prof., Department of Mathematics and Physics, University of Campania “Luigi Vanvitelli”, Caserta, Italy
- Maria Stella de Biase, Ph.D., Department of Mathematics and Physics, University of Campania “Luigi Vanvitelli”, Caserta, Italy
- Gaetano Settembre, Dr., Department of Mathematics, University of Bari Aldo Moro, Bari, Italy