Leveraging Cloud-Based Data for Generating Multisensor Flood Maps in Myanmar

Floods and other water-related disasters greatly impact local populations across many regions in Southeast Asia. Following the onset of flooding, remotely sensed geospatial data serves as a critical resource for flood maps that can be combined with other social and infrastructure information to aid in disaster response efforts. These maps are increasingly valuable in remote and isolated regions where information, communication, and infrastructure may be limited. However, these data have varying latencies, spatial, temporal, and radiometric resolutions, formats, and processing methods making it difficult for users to produce timely geospatial flood maps and use the data in a meaningful way. Given the large quantity of data needed to monitor these events, cloud-based resources offer a means to consolidate and streamline the process of accessing, processing, and visualizing flood maps generated from multiple satellite sensors in a more cost effective and computationally efficient way. This talk overviews the development of a near real-time flood service for Myanmar created by SERVIR-Mekong in partnership with Myanmar’s Department of Disaster Management that leverages Google Cloud and Google Earth Engine to generate fully automated, multi-sensor flood maps for the country of Myanmar. In this talk we will discuss the use of optical, SAR, and microwave remote sensing datasets and the data evaluation that led to the selection of cloud-hosted data and Google Earth Engine for large-scale geospatial processing. In addition we discuss lessons learned and in generated flood maps for the 2019 monsoon season. This talk demonstrates the use of cloud resources and GIS to generate multi-sensor flood maps at a larger scale using a consistent, automated methodology. The generated flood maps are available through a single, tailored mapviewer that has been customized based on end-user feedback and available for download and use within their own GIS, thus, allowing users to switch their focus from handling data to using data for decision making.