Quantifying Forest Fire and Post-Fire Vegetation Recovery in the Daxing’anling Area of Northeastern China Using Landsat Time-Series Data and Machine Learning

Quantifying Forest Fire and Post-Fire Vegetation Recovery in the Daxing’anling Area of Northeastern China Using Landsat Time-Series Data and Machine Learning

Many post-fire on-site factors, including fire severity, management strategies, topography, and local climate, are concerns for forest managers and recovery ecologists to formulate forest vegetation recovery plans in response to climate change. We used the Vegetation Change Tracker (VCT) algorithm t...

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Bibliographic Details
Main Authors: Jie Qiu, Heng Wang, Wenjuan Shen, Yali Zhang, Huiyi Su, Mingshi Li
Format: Article
Language:English
Published: MDPI AG 2021-02-01
Series:Remote Sensing
Subjects:
fire disturbance
post-fire recovery
VCT
SVM
SMLR
random forest
Online Access:https://www.mdpi.com/2072-4292/13/4/792

Internet

https://www.mdpi.com/2072-4292/13/4/792

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