Wasowski J., Bovenga F., Dijkstra T., Meng X., Nutricato R., Chiaradia M.T., 2014, Persistent Scatterers Interferometry Provides Insight on Slope Deformations and Landslide Activity in the Mountains of Zhouqu, Gansu, China, Landslide Science for a Safer Geoenvironment - Methods of Landslide Studies, edited by K. Sassa et al., pp. 359–364. CH-6330 Cham (ZG): Springer International Publishing, 2014,
URL: http://www.cnr.it/prodotto/i/309160

We present the results of Persistent Scatterers Interferometry (PSI) applied to investigate slope instabilities in a remote high mountain region of Southern Gansu, known to be prone to large magnitude (M7-8) earthquakes and catastrophic slope failures. The PSI processing of high resolution (~3 m) COSMO/SkyMed (CSK) satellite images produced spatially dense information (more than 1,000 PS/km2) on ground surface displacements in the area of Zhouqu, a town located in the Bailong River valley. A substantial portion of the radar targets showed significant displacements (from few to over 50 mm/year), denoting wide- spread occurrence of slope instabilities. In particular, the PSI results provided valuable information on the activity of some very large, apparently slow landslides that represent a persistent hazard to the local population and infrastructure. Monitoring movements of large long-lived landslides is important especially when, as in the case of the Bailong valley, they are known to undergo periods of increased activity resulting in river damming and disastrous flooding. Given the general lack of monitoring data on large landslides at Zhouqu and on other similar major failures that are common in Southern Gansu, the PSI- derived displacements offer unique information, which, following expert judgment, can be used for preliminary wide-area assessments of hazards linked to landslide activity. Fur- thermore, this study shows that with the high resolution CSK data resulting in high radar target density, PSI can also assist in slope/landslide-specific assessments.

Data from https://intranet.cnr.it/people/