Enhancing deep learning-based landslide detection from open satellite imagery via multisource data fusion of spectral, textural, and topographical features: a case study of old landslide detection in the Three Gorges Reservoir Area (TGRA)

Enhancing deep learning-based landslide detection from open satellite imagery via multisource data fusion of spectral, textural, and topographical features: a case study of old landslide detection in the Three Gorges Reservoir Area (TGRA)

Deep learning (DL) techniques are now predominant in landslide detection, aiding in risk assessment and disaster management. Detecting old landslides from open satellite imagery is challenging due to their altered shapes over time and minimal variation from the natural environment. Additional, DL mo...

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Bibliographic Details
Main Authors: Zhiyuan Ren, Junwei Ma, Jiayu Liu, Xin Deng, Guangcheng Zhang, Haixiang Guo
Format: Article
Language:English
Published: Taylor & Francis Group 2024-01-01
Series:Geocarto International
Subjects:
Landslide detection
multisource data fusion
ENVINet5
open-source satellite data
gradient-weighted class activation mapping (Grad-CAM)
Online Access:https://www.tandfonline.com/doi/10.1080/10106049.2024.2421224

Internet

https://www.tandfonline.com/doi/10.1080/10106049.2024.2421224

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