Landslide Identification from Post-Earthquake High-Resolution Remote Sensing Images Based on ResUNet–BFA

Landslide Identification from Post-Earthquake High-Resolution Remote Sensing Images Based on ResUNet–BFA

The integration of deep learning and remote sensing for the rapid detection of landslides from high-resolution remote sensing imagery plays a crucial role in post-disaster emergency response. However, the availability of publicly accessible deep learning datasets specifically for landslide detection...

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Bibliographic Details
Main Authors: Zhenyu Zhao, Shucheng Tan, Yiquan Yang, Qinghua Zhang
Format: Article
Language:English
Published: MDPI AG 2025-03-01
Series:Remote Sensing
Subjects:
post-earthquake landslide detection
landslide edge features
imagery landslide dataset
convolutional neural network
attention mechanism
Online Access:https://www.mdpi.com/2072-4292/17/6/995
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