Tripathy et al. (2025) Cloud-based flood mapping with Sentinel-1 SAR on Google Earth Engine: Insights from the global flood mapper

Identification

• Journal: Elsevier eBooks
• Year: 2025
• Date: 2025-12-05
• Authors: Pratyush Tripathy, Anil Kumar Agrawal, Simran Koul
• DOI: 10.1016/b978-0-443-33803-8.00045-7

Research Groups

• Department of Geography, University of California, Santa Barbara, CA, United States
• Monta Vista High School, Cupertino, CA, United States
• Bren School of Environmental Science & Management, University of California, Santa Barbara, CA, United States

Short Summary

This paper introduces a cloud-based flood mapping system utilizing Sentinel-1 SAR data on Google Earth Engine to provide rapid, scalable, and accurate flood information for disaster management. It aims to overcome the limitations of traditional flood monitoring methods by leveraging advanced geospatial technologies.

Objective

• To develop and demonstrate a cloud-based flood mapping system using Sentinel-1 Synthetic Aperture Radar (SAR) data on Google Earth Engine to enable rapid, accurate, and scalable identification of flood-affected areas for effective disaster response and resource allocation.

Study Configuration

• Spatial Scale: Global or large regional scale, designed for covering extensive areas.
• Temporal Scale: Near real-time or rapid response, aiming to provide insights within hours of a flood event.

Methodology and Data

• Models used: Cloud-based processing on Google Earth Engine for flood mapping.
• Data sources: Sentinel-1 Synthetic Aperture Radar (SAR) satellite imagery.

Main Results

• The provided text is an introduction and does not contain specific results or quantitative findings. It outlines the problem and the proposed solution's potential.

Contributions

• Provides a novel, cloud-based approach for rapid and scalable flood mapping, addressing the limitations of traditional, slow, localized, and expensive disaster monitoring methods.
• Leverages advanced geospatial technologies (Sentinel-1 SAR, Google Earth Engine) to enable near real-time situational awareness for flood disaster management globally.

Funding

• Not specified in the provided text.

Citation

@article{Tripathy2025Cloudbased,
  author = {Tripathy, Pratyush and Agrawal, Anil Kumar and Koul, Simran},
  title = {Cloud-based flood mapping with Sentinel-1 SAR on Google Earth Engine: Insights from the global flood mapper},
  journal = {Elsevier eBooks},
  year = {2025},
  doi = {10.1016/b978-0-443-33803-8.00045-7},
  url = {https://doi.org/10.1016/b978-0-443-33803-8.00045-7}
}