Mapping landslide phenomena in landlocked developing countries by means of satellite remote sensing data: the case of Dilijan (Armenia) area. Issue 2 (15th December 2017)

• Record Type: Journal Article
• Authors: Bianchini, Silvia; Raspini, Federico; Ciampalini, Andrea; Lagomarsino, Daniela; Bianchi, Marco; Bellotti, Fernando; Casagli, Nicola
• Is Part Of: Geomatics, natural hazards & risk. Volume 8:Issue 2(2017)
• Page Start: 225
• Page End: 241
• Publication Date: 2017-12-15
• Subjects: Landslide -- landslide inventory map -- susceptibility map -- remote sensing -- Armenia; Geomatics -- Periodicals; Geomatics; Periodicals; 526.905
• DOI: 10.1080/19475705.2016.1189459
• Languages: English
• ISSNs: 1947-5705

Abstract

ABSTRACT: Landslide detection and mapping are essential issues for reducing impact of such natural disasters, and for improving the future built-up expansion and planning strategies, especially in developing countries where a reasonable land-use design is an important concern for sustainable growth and environmental management. Armenia is a landlocked country and its urban development is strongly tied to the improvement of infrastructures, which must takes into account the environmental setting and the slope instability of the area, in order to identify risks and possible damages to settlements and economic activities. The use of satellite-based Earth Observation data has advanced significantly in the last decade and has turned out to be very useful for measuring and monitoring slow-moving surface deformation phenomena with millimetric precision. In this framework, this study aims at providing a remote sensing-based Landslide Inventory Map (LIM) and a Landslide Susceptibility Map (LSM) over Dilijan (Armenia) area, performed within the Secondary Cities Urban Development in Armenia project. In particular, LIM and LSM in the study area were produced by using ground deformation measurements derived from satellite Synthetic Aperture Radar (SAR) data, acquired by ALOS and ENVISAT sensors from 2003 up to 2010, and integrated with photo-interpretation of recent optical images and morphological analysis of Digital Elevation Model (DEM). Given the extensive presence of vegetation in the area of interest, satellite SAR images were processed to produce both SqueeSAR™ and Temporary Coherent Scatterers data, which are PSI (Persistent Scatterer Interferometry) data conceived as evolution of PSInSAR™ approach and particularly suited for non-urban and rural areas characterized by low density of coherent terrain benchmarks over time. Landslide mapping produced through this work identifies the most hazardous landslide-affected and landslide-prone areas around Dilijan city, and can be used for further estimating environmental risks for urban infrastructure development in the area.