Post-Fire Burned Area Detection Using Machine Learning and Burn Severity Classification with Spectral Indices in İzmir: A SHAP-Driven XAI Approach

This study was conducted to precisely map burned areas in fire-prone forest regions of İzmir and analyze the spatial distribution of wildfires. Using Sentinel-2 satellite imagery, burn severity was first classified using the dNBR and dNDVI indices. Subsequently, machine learning (ML) algorithms—RF,...

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Bibliografiset tiedot

Päätekijät:	Halil İbrahim Gündüz, Ahmet Tarık Torun, Cemil Gezgin
Aineistotyyppi:	Artigo
Kieli:	Inglês
Julkaistu:	MDPI AG 2025-03-01
Sarja:	Fire
Aiheet:	XAI SHAP wildfires burn severity Sentinel-2 machine learning
Linkit:	https://www.mdpi.com/2571-6255/8/4/121
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