Deep Learning-Based Landslide Recognition Incorporating Deformation Characteristics
Abstract
:1. Introduction
2. Study Area and Data
2.1. Study Area
2.2. Data and Preprocessing
3. Method
3.1. Selection of LCFs
3.2. FCADenseNet
3.3. Evaluation Metrics
3.4. Experiment Setting
4. Results and Analysis
4.1. Analysis of LCFs
4.2. LR Results
4.3. Improvement of FCADenseNet Performance by Deformation Rate
5. Discussion
5.1. Comparisions of the Model’s Effect
5.2. Influence of Deformation Rate on LR
5.3. Limitations and Future Work
6. Conclusions
Author Contributions
Funding
Data Availability Statement
Conflicts of Interest
References
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Data | Information | Number/Cloud Coverage | Resolution | Data Source |
---|---|---|---|---|
Sentinel-1 | 9 January 2021–29 May 2023 | 103 scenes | 5 m × 20 m | European Space Agency |
Sentinel-2 | 20230529T034541_T48RTR | 0.7637% | 10 m | |
20230529T034541_T48RUR | 1.2485% | |||
20230521T033539_T48RTQ | 0.0565% | |||
20230521T033539_T48RUQ | 0.4099% | |||
DEM | / | 12.5 m | Alaska Satellite Facility | |
Lithology | / | / | Geologic Map |
Deformation Rate | Elevation | Slope | Aspect | Curve | Lithology | |
---|---|---|---|---|---|---|
VIF | 1.074 | 1.044 | 1.031 | 1.002 | 1.007 | 1.028 |
TOL | 0.931 | 0.957 | 0.970 | 0.998 | 0.993 | 0.973 |
Pre | Rec | F1 | Kappa | MIoU | |
---|---|---|---|---|---|
FCN | 0.6870 | 0.5354 | 0.6018 | 0.6002 | 0.7136 |
U-Net | 0.4653 | 0.6908 | 0.5561 | 0.5543 | 0.6901 |
FC_DenseNet | 0.6312 | 0.7043 | 0.6658 | 0.6599 | 0.7479 |
FCADenseNet | 0.8381 | 0.6972 | 0.7611 | 0.7602 | 0.8062 |
Pre | Rec | F1 | Kappa | MIoU | |
---|---|---|---|---|---|
RS | 0.6614 | 0.6878 | 0.6743 | 0.6729 | 0.7529 |
RS-DR | 0.8381 | 0.6972 | 0.7611 | 0.7602 | 0.8062 |
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Li, Z.; Shi, A.; Li, X.; Dou, J.; Li, S.; Chen, T.; Chen, T. Deep Learning-Based Landslide Recognition Incorporating Deformation Characteristics. Remote Sens. 2024, 16, 992. https://doi.org/10.3390/rs16060992
Li Z, Shi A, Li X, Dou J, Li S, Chen T, Chen T. Deep Learning-Based Landslide Recognition Incorporating Deformation Characteristics. Remote Sensing. 2024; 16(6):992. https://doi.org/10.3390/rs16060992
Chicago/Turabian StyleLi, Zhihai, Anchi Shi, Xinran Li, Jie Dou, Sijia Li, Tingxuan Chen, and Tao Chen. 2024. "Deep Learning-Based Landslide Recognition Incorporating Deformation Characteristics" Remote Sensing 16, no. 6: 992. https://doi.org/10.3390/rs16060992
APA StyleLi, Z., Shi, A., Li, X., Dou, J., Li, S., Chen, T., & Chen, T. (2024). Deep Learning-Based Landslide Recognition Incorporating Deformation Characteristics. Remote Sensing, 16(6), 992. https://doi.org/10.3390/rs16060992