Wasowski, J.; Bovenga, F.; Nutricato, R.; Nitti, D. O.; Chiaradia, M. T., 2015, APPLICATIONS OF MEDIUM C-BAND AND HIGH RESOLUTION X-BAND MULTI-TEMPORAL INTERFEROMETRY IN LANDSLIDE INVESTIGATIONS, International Conference on Sensors & Models in Remote Sensing & Photogrammetry, pp. 737–743, 23-25/11/2015,
URL: http://www.cnr.it/prodotto/i/399195

With the increasing quantity and quality of the imagery available from a growing number of SAR satellites and the improved processing algorithms, multi-temporal interferometry (MTI) is expected to be commonly applied in landslide studies. MTI can now provide long-term (years), regular (weekly-monthly), precise (mm) measurements of ground displacements over large areas (thousands of km(2)), at medium (similar to 20 m) to high (up to 1-3 m) spatial resolutions, combined with the possibility of multi-scale (regional to local) investigations, using the same series of radar images. We focus on the benefits as well as challenges of multi-sensor and multi-scale investigations by discussing MTI results regarding two landslide prone regions with distinctly different topographic, climatic and vegetation conditions (mountains in Central Albania and Southern Gansu, China), for which C-band (ERS or ENVISAT) and X-band COSMO-SkyMed (CSK) imagery was available (all in Stripmap descending mode). In both cases X-band MTI outperformed C-band MTI by providing more valuable information for the regional to local scale detection of slope deformations and landslide hazard assessment. This is related to the better spatial-temporal resolutions and more suitable incidence angles (40 degrees-30 degrees versus 23 degrees) of CSK data While the use of medium resolution imagery may be appropriate and more cost-effective in reconnaissance or regional scale investigations, high resolution data could be preferentially exploited when focusing on urbanized landslides or potentially unstable slopes in urban/peri-urban areas, and slopes traversed by lifelines and other engineering structures.

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