Huang (2025) Future challenges and opportunities in data-driven Earth observation

Identification

• Journal: Elsevier eBooks
• Year: 2025
• Date: 2025-12-05
• Authors: Xiao Huang
• DOI: 10.1016/b978-0-443-33803-8.00038-x

Research Groups

Department of Environmental Sciences, Emory University

Short Summary

This chapter reviews the current landscape of Earth observation (EO) technologies in disaster management, addressing advancements, data volume challenges, and future opportunities presented by emerging technologies like quantum computing, blockchain, and 5G.

Objective

• To analyze the current state, challenges, and future opportunities of data-driven Earth observation technologies for enhancing disaster management capabilities.

Study Configuration

• Spatial Scale: From sub-meter resolution (for specific damage assessment) to global coverage (for broad disaster monitoring).
• Temporal Scale: Real-time monitoring and assessment, with frequent revisit times for continuous observation.

Methodology and Data

• Models used: Not explicitly specified; the chapter discusses the potential for accelerated disaster modeling and scenario simulations using quantum computing.
• Data sources: Satellite systems (next-generation, miniaturized constellations like CubeSats and SmallSats), Unmanned Aerial Vehicles (UAVs), and ground-based sensors.

Main Results

• Earth observation technologies are fundamental for disaster management, offering unparalleled precision for monitoring, prediction, and response.
• While advancements provide high-resolution and frequent data, the resulting data volume poses significant processing and analysis challenges.
• Emerging technologies such as quantum computing, blockchain, and 5G networks are identified as critical for accelerating data processing, ensuring secure data sharing, and enabling rapid data transmission, thereby enhancing future disaster management capabilities.

Contributions

• This work provides a forward-looking synthesis of the evolving role of data-driven Earth observation in disaster management, identifying key technological advancements, current limitations, and transformative future opportunities, particularly with respect to quantum computing, blockchain, and 5G.

Funding

• Not specified in the provided text.

Citation

@article{Huang2025Future,
  author = {Huang, Xiao},
  title = {Future challenges and opportunities in data-driven Earth observation},
  journal = {Elsevier eBooks},
  year = {2025},
  doi = {10.1016/b978-0-443-33803-8.00038-x},
  url = {https://doi.org/10.1016/b978-0-443-33803-8.00038-x}
}