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Double-Step U-Net: A Deep Learning-Based Approach for the Estimation of Wildfire Damage Severity through Sentinel-2 Satellite Data

Wildfire damage severity census is a crucial activity for estimating monetary losses and for planning a prompt restoration of the affected areas. It consists in assigning, after a wildfire, a numerical damage/severity level, between 0 and 4, to each sub-area of the hit area. While burned area identi...

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Hoofdauteurs: Alessandro Farasin, Luca Colomba, Paolo Garza
Formaat: Artigo
Taal:Inglês
Gepubliceerd in: MDPI AG 2020-06-01
Reeks:Applied Sciences
Onderwerpen:
copernicus
sentinel
satellite
wildfire
severity
U-Net
Online toegang:https://www.mdpi.com/2076-3417/10/12/4332
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