NDLI: The effectiveness of high-resolution LiDAR data combined with PSInSAR data in landslide study

Content Provider	Springer Nature Link
Author	Ciampalini, Andrea Raspini, Federico Frodella, William Bardi, Federica Bianchini, Silvia Moretti, Sandro
Copyright Year	2015
Abstract	The spatial resolution of digital elevation models (DEMs) is an important factor for reliable landslide studies. Multi-interferometric techniques such as persistent scatterer interferometric synthetic aperture radar (PSInSAR) are used to evaluate the landslide state of activity and its ground deformation velocity, which is commonly measured along the satellite line of sight (LOS). In order to compare velocities measured by different satellites in different periods, their values can be projected along the steepest slope direction, which is the most probable direction of real movement. In order to achieve this result, DEM-derived products are needed. In this paper, the effectiveness of different DEM resolutions was evaluated in order to project ground deformation velocities measured by means of PSInSAR technique in two different case studies in the Messina Province (Sicily, southern Italy): San Fratello and Giampilieri. Three DEMs were used: (i) a 20-m resolution DEM of the Italian Military Geographic Institute (IGM), (ii) a 2-m resolution DEM derived from airborne laser scanning (ALS) light detection and ranging (LiDAR) data for the San Fratello 2010 landslide, and (iii) a 1-m resolution DEM derived from ALS LiDAR data for the area of Giampilieri. The evaluation of the applied method effectiveness was performed by comparing the DEMs elevation with those of each single permanent scatterer (PS) and projecting the measured velocities along the steepest slope direction. Results highlight that the higher DEM resolution is more suitable for this type of analysis; in particular, the PS located nearby the watershed divides is affected by geometrical problems when their velocities are projected along the steepest slope.
Starting Page	399
Ending Page	410
Page Count	12
File Format	PDF
ISSN	1612510X
Journal	Landslides
Volume Number	13
Issue Number	2
e-ISSN	16125118
Language	English
Publisher	Springer Berlin Heidelberg
Publisher Date	2015-12-05
Publisher Place	Berlin, Heidelberg
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Landslide PSInSAR DEM Velocity projection LiDAR Natural Hazards Geography Agriculture Civil Engineering
Content Type	Text
Resource Type	Article
Subject	Geotechnical Engineering and Engineering Geology

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