SUBMIT ONLINE: https://www.easychair.org/conferences/?conf=prai2026  (Please choose Special Session 16)

This special session focuses on multimodal data fusion and intelligent analysis for remote sensing applications. With the rapid development of Earth observation technologies, massive volumes of heterogeneous data have become available, including satellite imagery, temporal observations, and environmental variables such as climate and meteorological data. Effectively integrating these diverse data sources is essential for improving the accuracy, robustness, and interpretability of remote sensing systems. This session aims to explore recent advances in artificial intelligence and data-driven approaches that enable joint modeling of multimodal and spatiotemporal information. Topics of interest include multimodal learning, spatiotemporal analysis, data fusion strategies, and intelligent image processing techniques. Particular attention will be given to integrating remote sensing data with auxiliary sources such as climate forecast systems and environmental models to enhance real-world applications.

Chairs:
Dekai Li Hainan University, China lidekai@hainanu.edu.cn		Uzair Aslam Bhatti Hainan University, China uzair@hainanu.edu.cn

Topics of interest include, but are not limited to:

• Multimodal data fusion for remote sensing
• Integration of remote sensing and environmental/climate data
• Spatiotemporal modeling and analysis
• Intelligent image processing and enhancement
• Change detection and time-series analysis
• Deep learning for geospatial data
• Data-driven Earth observation systems
• Environmental monitoring and disaster assessment
• Agricultural and urban applications