Deep Learning Based Burnt Area Mapping Using Sentinel 1 for the Santa Cruz Mountains Lightning Complex (CZU) and Creek Fires 2020

Deep Learning Based Burnt Area Mapping Using Sentinel 1 for the Santa Cruz Mountains Lightning Complex (CZU) and Creek Fires 2020

The study presented here builds on previous synthetic aperture radar (SAR) burnt area estimation models and presents the first U-Net (a convolutional network architecture for fast and precise segmentation of images) combined with ResNet50 (Residual Networks used as a backbone for many computer visio...

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Bibliographic Details
Main Authors:	Harrison Luft, Calogero Schillaci, Guido Ceccherini, Diana Vieira, Aldo Lipani
Format:	Article
Language:	English
Published:	MDPI AG 2022-10-01
Series:	Fire
Subjects:	deep learning fire mapping synthetic aperture radar land cover ResNet
Online Access:	https://www.mdpi.com/2571-6255/5/5/163

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