Deep Learning Approaches for Wildfire Severity Prediction: A Comparative Study of Image Segmentation Networks and Visual Transformers on the EO4WildFires Dataset

Deep Learning Approaches for Wildfire Severity Prediction: A Comparative Study of Image Segmentation Networks and Visual Transformers on the EO4WildFires Dataset

This paper investigates the applicability of deep learning models for predicting the severity of forest wildfires, utilizing an innovative benchmark dataset called EO4WildFires. EO4WildFires integrates multispectral imagery from Sentinel-2, SAR data from Sentinel-1, and meteorological data from NASA...

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Bibliographic Details
Main Authors: Dimitris Sykas, Dimitrios Zografakis, Konstantinos Demestichas
Format: Article
Language:English
Published: MDPI AG 2024-10-01
Series:Fire
Subjects:
forest wildfires
earth observation
remote sensing
machine learning
deep learning
training dataset
Online Access:https://www.mdpi.com/2571-6255/7/11/374
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