Landslide Inventory Mapping Based on Independent Component Analysis and UNet3+: A Case of Jiuzhaigou, China
Landslide inventory mapping (LIM) is an important prerequisite for disaster emergency rescue and landslide sensitivity analysis. It has been proven that convolutional neural networks have better performance for LIM than traditional machine learning methods such as support vector machines, and random...
| Main Authors: | , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2024-01-01
|
| Series: | IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10342839/ |