Details

Autor(en) / Beteiligte

• Bonì, Roberta
• Bordoni, Massimiliano
• Colombo, Alessio
• Lanteri, Luca
• Meisina, Claudia

Titel

Landslide state of activity maps by combining multi-temporal A-DInSAR (LAMBDA)

Ist Teil von

• Remote sensing of environment, 2018-11, Vol.217, p.172-190

Ort / Verlag

New York: Elsevier Inc

Erscheinungsjahr

2018

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• In this paper, a new methodology was developed to automatically update Landslide state of Activity Maps by combining multi-temporal A-DInSAR data (LAMBDA). LAMBDA procedure was tested using ERS-1/2 (1992–2000), Radarsat-1/2 (2003–2009) and COSMO-SkyMed data (2011–2014) over an area of 2199 km2 located in Alps context of Piedmont region (north-western Italy). For the first time, a multidimensional landslide activity matrix was implemented to update the landslide state of activity during the monitored time span. For the definition of the state of activity, the representative velocity of each landslide was divided by the standard deviation of the velocities along the slope of the whole dataset. Thus, a common stability threshold of ±1 was introduced for multi-sensors A-DInSAR data, allowing to distinguish a phenomenon with stable targets (PS-DS) or unstable PS-DS. By combining activity classes estimated during different time spans allows to determine if a phenomenon is active, reactivated, or dormant. Furthermore, an innovative confidence degree assessment was carried out to verify the reliability of the procedure, by considering the measuring points distribution and the variability of the movements for each landslide. The results were validated using the landslide inventory of the study area and in-situ monitoring systems for representative case studies. Thanks to this approach an updated state of activity until 2014 was assigned to 507 landslides out the 1657 which were previously mapped in the study area. •A new methodology for updating Landslide state of Activity named LAMBDA procedure•LAMBDA is tested in the Alps context of Piedmont using multi-temporal A-DInSAR data.•Update of the state of activity of 507 slow-moving landslides until 2014•Two indexes of confidence degree to the state of activity for each landslide•Results are consistent with the landslides inventory and in situ field evidences.