Enabling global processing of reference water products for flood mapping using Kubernetes and STAC

Abstract

A key factor in successful flood mapping is the fast and easy access to water extent information at normal, non-flood conditions. In this study, we propose a fully automated and scalable methodology for generating and publishing information on permanent and seasonal surface water extent by leveraging cloud technologies such as Docker and Kubernetes. Products can be computed at global scale and made accessible free of cost via standardized interfaces. With this approach, the disaster response community benefits from easy data access and flexible integration into automated rapid mapping workflows. To showcase our approach, we generate reference water information in the scope of the 2022 flooding in Pakistan.