Mapping Complex Landslide Scars Using Deep Learning and High-Resolution Topographic Derivatives from LiDAR Data in Quebec, Canada
This study evaluates deep learning (DL) models, particularly ResU-Net with attention mechanisms, for mapping landslides in Quebec, Canada, utilizing high-resolution digital elevation model (HRDEM) data and its seven derivatives (slope, aspect, hillshade, curvature, ruggedness, surface area ratio, an...
Saved in:
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2024-12-01
|
| Series: | Canadian Journal of Remote Sensing |
| Subjects: | |
| Online Access: | http://dx.doi.org/10.1080/07038992.2024.2418087 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|