4.7 Article

Landslide Displacement Monitoring by a Fully Polarimetric SAR Offset Tracking Method

期刊

REMOTE SENSING
卷 8, 期 8, 页码 -

出版社

MDPI
DOI: 10.3390/rs8080624

关键词

landslide monitoring; displacement; offset tracking; PolSAR

资金

  1. National Natural Science Foundation of China [41371335]
  2. National Basic Research Program of China [2013CB733303]
  3. Natural Science Foundation of Hunan Province, China [2016JJ2141]

向作者/读者索取更多资源

Landslide monitoring is important for geological disaster prevention, where Synthetic Aperture Radar (SAR) images have been widely used. Compared with the Interferometric SAR (InSAR) technique, intensity-based offset tracking methods (e.g., Normalized Cross-Correlation method) can overcome the limitation of InSAR's maximum detectable displacement. The normalized cross-correlation (NCC) method, based on single-channel SAR images, estimates azimuth and range displacement by using statistical correlation between the matching windows of two SAR images. However, the matching windows-especially for the boundary area of landslide-always contain pixels with different moving characteristics, affecting the precision of displacement estimation. Based on the advantages of polarimetric scattering properties, this paper proposes a fully polarimetric SAR (PolSAR) offset tracking method for improvement of the precision of landslide displacement estimation. The proposed method uses the normalized inner product (NIP) of the two temporal PolSAR Pauli scattering vectors to evaluate their similarity, then retrieve the surface displacement of the Slumgullion landslide located in southwestern Colorado, USA. A pair of L-band fully polarimetric SAR images acquired by the Jet Propulsion Laboratory's Uninhabited Aerial Vehicle Synthetic Aperture Radar (UAVSAR) system are selected for experiment. The results show that the Slumgullion landslide's moving velocity during the monitoring time ranges between 1.6-10.9 mm/d, with an average velocity of 6.3 mm/d. Compared with the classical NCC method, results of the proposed method present better performance in the sub-pixel estimation. Furthermore, it performs better when estimating displacement in the area around the landslide boundaries.

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