Title of article :
Large-area landslide detection and monitoring with ALOS/PALSAR imagery data over Northern California and Southern Oregon, USA
Author/Authors :
Zhao، نويسنده , , Chaoying and Lu، نويسنده , , Zhong and Zhang، نويسنده , , Qin and de la Fuente، نويسنده , , Juan، نويسنده ,
Issue Information :
روزنامه با شماره پیاپی سال 2012
Pages :
12
From page :
348
To page :
359
Abstract :
Multi-temporal ALOS/PALSAR images are used to automatically investigate landslide activity over an area of ~ 200 km by ~ 350 km in northern California and southern Oregon. Interferometric synthetic aperture radar (InSAR) deformation images, InSAR coherence maps, SAR backscattering intensity images, and a DEM gradient map are combined to detect active landslides by setting individual thresholds. More than 50 active landslides covering a total of about 40 km2 area are detected. Then the short baseline subsets (SBAS) InSAR method is applied to retrieve time-series deformation patterns of individual detected landslides. Down-slope landslide motions observed from adjacent satellite tracks with slightly different radar look angles are used to verify InSAR results and measurement accuracy. Comparison of the landslide motion with the precipitation record suggests that the landslide deformation correlates with the rainfall rate, with a lag time of around 1–2 months between the precipitation peak and the maximum landslide displacement. The results will provide new insights into landslide mechanisms in the Pacific Northwest, and facilitate development of early warning systems for landslides under abnormal rainfall conditions. Additionally, this method will allow identification of active landslides in broad areas of the Pacific Northwest in an efficient and systematic manner, including remote and heavily vegetated areas difficult to inventory by traditional methods.
Keywords :
Landslide , Monitoring , detection , Synthetic aperture radar (SAR) , ALOS/PALSAR , Interferometric SAR (InSAR)
Journal title :
Remote Sensing of Environment
Serial Year :
2012
Journal title :
Remote Sensing of Environment
Record number :
1632393
Link To Document :
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