An Integration Framework of Google Earth Engine as a Cloud Processing Engine in a Web-GIS Architecture for Flood Risk Analysis - Ni Luh Suryani Agustini; Ketut Agus Seputra; Pariwate Varnakovida; Kadek Yota Ernanda Aryanto (Jurnal Nasional Pendidikan Teknik Informatika: JANAPATI, 2026)
Flooding is a significant hydrometeorological hazard in Southeast Asia, causing severe social, economic, and environmental impacts. Effective flood risk management is hindered by the lack of timely and accurate information, especially in areas such as Nakhon Pathom, Thailand, where seasonal floods frequently disrupt settlements and infrastructure. This study addresses this issue by proposing an integration framework that combines Google Earth Engine (GEE), a cloud-based geospatial analytics platform, with Web-GIS architecture for flood risk analysis. The integration aims to process large-scale, multi-temporal satellite data, such as Sentinel and Landsat imagery, to map flood-prone areas, analyze rainfall, and assess historical flood events. The system leverages GEE’s cloud computing capabilities to perform spatial analyses and deliver results via an interactive Web GIS interface. The architecture includes a proxy server to enable secure, efficient communication between the Web-GIS frontend and the GEE backend. By adopting this cloud-based approach, the system improves scalability, enhances data processing efficiency, and ensures accessibility via web browsers on various devices. The study shows that this integrated framework enables real-time flood risk assessments and dynamic visualizations, supporting decision-making in disaster management. This approach can be generalized to other disaster risk analyses, offering a scalable solution for flood mitigation and adaptation to climate change.