Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery

Fully Convolutional Neural Network for Rapid Flood Segmentation in Synthetic Aperture Radar Imagery

Rapid response to natural hazards, such as floods, is essential to mitigate loss of life and the reduction of suffering. For emergency response teams, access to timely and accurate data is essential. Satellite imagery offers a rich source of information which can be analysed to help determine region...

Full description

Bibliographic Details
Main Authors: Edoardo Nemni, Joseph Bullock, Samir Belabbes, Lars Bromley
Format: Article
Language:English
Published: MDPI AG 2020-08-01
Series:Remote Sensing
Subjects:
microwave remote sensing
rapid mapping
disaster response
flood mapping
image segmentation
machine learning
Online Access:https://www.mdpi.com/2072-4292/12/16/2532

Similar Items

Similar Items