Evaluating the potential of burn severity mapping and transferability of Copernicus EMS data using Sentinel-2 imagery and machine learning approaches

Evaluating the potential of burn severity mapping and transferability of Copernicus EMS data using Sentinel-2 imagery and machine learning approaches

The abiotic and biotic conditions in forest ecosystems can be significantly influenced by forest fires. However, difficulties in policy decisions for restoration inevitably occur in the absence of information on the damaged forests, such as location, area, and burn severity. In this study, eight spe...

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Bibliographic Details
Main Authors: Kyungil Lee, Byeongcheol Kim, Seonyoung Park
Format: Article
Language:English
Published: Taylor & Francis Group 2023-12-01
Series:GIScience & Remote Sensing
Subjects:
forest fires
burn severity
sentinel-2
machine learning
copernicus ems data
Online Access:http://dx.doi.org/10.1080/15481603.2023.2192157

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