Deep Convolutional Neural Network for Flood Extent Mapping Using Unmanned Aerial Vehicles Data

Deep Convolutional Neural Network for Flood Extent Mapping Using Unmanned Aerial Vehicles Data

Flooding is one of the leading threats of natural disasters to human life and property, especially in densely populated urban areas. Rapid and precise extraction of the flooded areas is key to supporting emergency-response planning and providing damage assessment in both spatial and temporal measure...

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Bibliographic Details
Main Authors: Asmamaw Gebrehiwot, Leila Hashemi-Beni, Gary Thompson, Parisa Kordjamshidi, Thomas E. Langan
Format: Article
Language:English
Published: MDPI AG 2019-03-01
Series:Sensors
Subjects:
remote sensing
convolutional neural networks
floodplain mapping
fully convolutional network
unmanned aerial vehicles
geospatial data processing
Online Access:https://www.mdpi.com/1424-8220/19/7/1486

Internet

https://www.mdpi.com/1424-8220/19/7/1486

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