Machine Learning-Based Forest Burned Area Detection with Various Input Variables: A Case Study of South Korea

Machine Learning-Based Forest Burned Area Detection with Various Input Variables: A Case Study of South Korea

Recently, an increase in wildfire incidents has caused significant damage from economical, humanitarian, and environmental perspectives. Wildfires have increased in severity, frequency, and duration because of climate change and rising global temperatures, resulting in the release of massive volumes...

Full description

Bibliographic Details
Main Authors: Changhui Lee, Seonyoung Park, Taeheon Kim, Sicong Liu, Mohd Nadzri Md Reba, Jaehong Oh, Youkyung Han
Format: Article
Language:English
Published: MDPI AG 2022-10-01
Series:Applied Sciences
Subjects:
forest fire burned area detection
Sentinel-2
Random Forest
LightGBM
U-Net
input variables analysis
Online Access:https://www.mdpi.com/2076-3417/12/19/10077

Similar Items

Similar Items