Name
Title | ||
|---|---|---|
Rapid and Automatic Detection of New Potential Landslide Based on Phase-Gradient DInSAR |
Abstract | ||
|---|---|---|
Although the widely used time-series interferometric synthetic aperture radar (InSAR) technology makes up for the shortcomings of traditional geological investigation, such as small coverage and low efficiency, it cannot achieve rapid and dynamic detection of new potential landslide due to its long data processing time and insensitivity to short-term new displacement. In this letter, a rapid method for automatically detecting new potential landslides in wide area is proposed. Phase-gradient processing is performed based on the differential synthetic aperture radar interferometry (DInSAR) results to automatically detect the potential landslide, in which the influence from geometric distortion, water, noise from low-coherence area, and other errors are analyzed and removed. This method was performed in the Maoergai Reservoir Area where many potential landslides newly emerged during the impoundment period as the great water-level fluctuations. As a result, seven potential landslides with continuous deformation and relatively large deformation were detected. The error source was analyzed and removed. In the validation, an overall accuracy of up to 81% was achieved by comparing the results with the manual detection. This method provides a new way for rapid and automatic detection of new displacements in wide area, especially for the area (e.g., reservoir area) with dynamic and rapid detection needs. |
Year | DOI | Venue |
|---|---|---|
2022 | 10.1109/LGRS.2022.3207064 | IEEE GEOSCIENCE AND REMOTE SENSING LETTERS |
Keywords | DocType | Volume |
Terrain factors, Synthetic aperture radar, Reservoirs, Strain, Interferometry, Coherence, Image edge detection, Automatic detection, differential synthetic aperture radar interferometry (DInSAR), new potential landslide, phase gradient | Journal | 19 |
ISSN | Citations | PageRank |
1545-598X | 0 | 0.34 |
References | Authors | |
0 | 7 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yue Shen | 1 | 0 | 0.34 |
| Keren Dai | 2 | 0 | 0.34 |
| Mingtang Wu | 3 | 0 | 0.34 |
| Guanchen Zhuo | 4 | 0 | 0.34 |
| Min Wang | 5 | 76 | 27.77 |
| Teng Wang | 6 | 69 | 6.25 |
| Qiang Xu | 7 | 6 | 7.23 |