Global flood extent segmentation in optical satellite images.

ABSTRACT: Floods are among the most destructive extreme events that exist, being the main cause of people affected by natural disasters. In the near future, estimated flood intensity and frequency are projected to increase. In this context, automatic and accurate satellite-derived flood maps are key for fast emergency response and damage assessment. However, current approaches for operational flood mapping present limitations due to cloud coverage on acquired satellite images, the accuracy of flood detection, and the generalization of methods across different geographies. In this work, a machine learning framework for operational flood mapping from optical satellite images addressing these problems is presented. It is based on a clouds-aware segmentation model trained in an extended version of the W

SUBMITTER: Portales-Julia E 

PROVIDER: S-EPMC10661555 | biostudies-literature | 2023 Nov

REPOSITORIES: biostudies-literature