Convolutional neural network-based deep learning for landslide susceptibility mapping in the Bakhtegan watershed
Abstract Landslides pose a significant threat to infrastructure, ecosystems, and human safety, necessitating accurate and efficient susceptibility assessment methods. Traditional models often struggle to capture the complex spatial dependencies and interactions between geological and environmental f...
Saved in:
| Main Authors: | Li Feng, Maosheng Zhang, Yimin Mao, Hao Liu, Chuanbo Yang, Ying Dong, Yaser A. Nanehkaran |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-04-01
|
| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-96748-3 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Landslide susceptibility assessment using the frequency ratio model in the Mae Chan River watershed, northern Thailand
by: Pichawut Manopkawee, et al.
Published: (2025-01-01) -
A hybrid data-driven approach for rainfall-induced landslide susceptibility mapping: Physically-based probabilistic model with convolutional neural network
by: Hong-Zhi Cui, et al.
Published: (2025-08-01) -
Multi-scale convolutional neural networks (CNNs) for landslide inventory mapping from remote sensing imagery and landslide susceptibility mapping (LSM)
by: Baoyi Zhang, et al.
Published: (2024-12-01) -
Applications and Advancements of Spaceborne InSAR in Landslide Monitoring and Susceptibility Mapping: A Systematic Review
by: Yusen Cheng, et al.
Published: (2025-03-01) -
Ecohydrological Analysis in Watersheds of Mountain Areas of São Paulo State Coastal, Brazil
by: Saulo Folharini, et al.
Published: (2022-12-01)