Machine Learning and Deep Learning for Wildfire Spread Prediction: A Review

Fire, Journal Year: 2024, Volume and Issue: 7(12), P. 482 - 482

Published: Dec. 18, 2024

The increasing frequency and intensity of wildfires highlight the need to develop more efficient tools for firefighting management, particularly in field wildfire spread prediction. Classical models have relied on mathematical empirical approaches, which trouble capturing complexity fire dynamics suffer from poor flexibility static assumptions. emergence machine learning (ML) and, specifically, deep (DL) has introduced new techniques that significantly enhance prediction accuracy. ML models, such as support vector machines ensemble use tabular data points identify patterns predict behavior. However, these often struggle with dynamic nature wildfires. In contrast, DL convolutional neural networks (CNNs) recurrent (CRNs), excel at handling spatiotemporal complexities data. CNNs are effective analyzing spatial satellite imagery, while CRNs suited both sequential data, making them highly performant predicting This paper presents a systematic review recent developed prediction, detailing commonly used datasets, improvements achieved, limitations current methods. It also outlines future research directions address challenges, emphasizing potential play an important role management mitigation strategies.

Language: Английский

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Mbda-net: a building damage assessment model based on a multi-scale fusion network

Signal Image and Video Processing, Journal Year: 2024, Volume and Issue: unknown

Published: Sept. 10, 2024

Language: Английский

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Flood detection in UAV images using PSPNet and uncertainty quantification with Monte-Carlo Dropout technique

Deleted Journal, Journal Year: 2024, Volume and Issue: 13(4), P. 41 - 56

Published: June 1, 2024

Language: Английский

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Deep Learning Models for Enhanced Forest-Fire Prediction at Mount Kilimanjaro, Tanzania: Integrating Satellite Images, Weather Data and Human Activities

Natural Hazards Research, Journal Year: 2024, Volume and Issue: unknown

Published: Dec. 1, 2024

Language: Английский

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Application of Interpretable Convolutional Neural Networks Incorporating ASPP Mechanism in Wildfire Spread Prediction

Computer Science and Application, Journal Year: 2024, Volume and Issue: 14(12), P. 171 - 179

Published: Jan. 1, 2024

Language: Английский

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