Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis
Abstract
:1. Introduction
2. Background
3. Methods
- (1)
- Data ingestion and preprocessing (Figure 2a), and change detection (Figure 2b), discussed in Section 3.1;
- (2)
- Object-based image analysis, including object feature extraction, as well as image segmentation and object classification (Figure 2d), by making use of polarimetric decomposition (Figure 2c), discussed in Section 3.2.
3.1. Preprocessing of Intensity Image and Change Detection
3.2. Object-Based Image Analysis
3.2.1. Object-Based Feature Extraction
3.2.2. Image Segmentation and Object Classification
3.3. Study Area
4. Results and Discussion
5. Conclusions and Outlook
Author Contributions
Funding
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Event and Date | SAR Data | Acquisition Date | Mode | Image Polarization | Resolution |
---|---|---|---|---|---|
Typhoon Morakot | ASAR | 2009/07/15 | Descending | VV, HH | 22 m |
August 2009 | (AP mode) | 2009/08/19 | Descending | VV, VH |
Areas with Landslides | Areas Devoid of Landslides | |
---|---|---|
Statistical Indices | ||
Standard Deviation | 0.78–1.25 | 0.64–0.74 |
Skewness | 0.56–1.54 | 1.57–1.86 |
Polarimetric Decomposition | ||
Entropy (P) | 0.52–0.71 | 0.74–0.84 |
Anisotropy | 0.59–0.76 | 0.45–0.56 |
Alpha | 12.76–20.98 | 22.23–28.04 |
Spatial Autocorrelation | ||
Getis-Ord Gi | 0.47–1.34 | 0.00–0.44 |
Moran’s I | 0.77–2.39 | 0.49–0.71 |
Geary’s C | 0.68–0.82 | 0.50–0.66 |
Texture Indicators | ||
Contrast | 55.56–113.44 | 37.56–52.69 |
Dissimilarity | 5.81–8.51 | 4.81–5.77 |
Homogeneity | 0.11–0.16 | 0.16–0.19 |
Entropy (T) | 3.74–3.77 | 3.72–3.75 |
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Lin, S.-Y.; Lin, C.-W.; van Gasselt, S. Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis. Remote Sens. 2021, 13, 644. https://doi.org/10.3390/rs13040644
Lin S-Y, Lin C-W, van Gasselt S. Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis. Remote Sensing. 2021; 13(4):644. https://doi.org/10.3390/rs13040644
Chicago/Turabian StyleLin, Shih-Yuan, Cheng-Wei Lin, and Stephan van Gasselt. 2021. "Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis" Remote Sensing 13, no. 4: 644. https://doi.org/10.3390/rs13040644
APA StyleLin, S. -Y., Lin, C. -W., & van Gasselt, S. (2021). Processing Framework for Landslide Detection Based on Synthetic Aperture Radar (SAR) Intensity-Image Analysis. Remote Sensing, 13(4), 644. https://doi.org/10.3390/rs13040644