LivingPlanetSymposium13 17May2019Milano

BEYOND is participating in the Living Planet Symposium in the session "Sentinels and Copernicus Contributing Missions for Cultural & Natural Heritage (1)".On Thursday 16 May, our colleague Aikaterini Karagianopoulou will give an oral presentation on " Innovative EO based regional-scale, landslide run-out assessment

for the conservation and protection  of Cultural and Natural Heritage sites (CNHs)".


Northern Greece is considered as the birthplace of a significant number of Cultural and Natural Heritage (CNH) sites. However, due to mountainous topography, intense seismic activity, and flash rainfall events, the regional landscape faces severe impacts of damages and losses due to frequent natural disasters, such us landslides. This way, in the area of our interest there are natural Wildlife Refuges and historical monuments of the Byzantine period and the Bronze Age that are at risk. Thus, the estimation of large-scale landslide susceptibility in the region, coupled with the assessment of the propagation of the runout distance of an active landslide is of a paramount importance. Such critical information provides to national and regional authorities the landslide hotspot areas, assisting decision makers in evidence-based disaster preparedness activities and planning of mitigation measures. 

Therefore, the main scope of our work is to investigate the contribution of Earth Observation (EO) data and GIS to the estimation of landslide susceptibility and runout distance assessment, in order to provide useful tools for enhancing the resilience of CNH sites. 

Firstly, we use Persistent Scatterer Interferometry (PSI) methods to estimate the ground deformation pattern and trends over the last 20 years (1998-2018) in order to construct a new landslide inventory map for the entire area. This dataset is used as a validation tool for the subsequent landslide susceptibility analysis. We then compare two semi-quantitative methods; the Norwegian Geotechnical Institute (NGI) approach and the statistical method Weights of Evidence (WoE). We consider as predisposing and triggering factors the ground conditions (geological map of 1:300.000 scale), the local inclination resulted from a medium resolution DEM (SRTM), the vegetation cover produced from Sentinel-2 data, and the estimation of extreme rainfall distribution of 100-years, based on a CHIRPS monthly rainfall time-series analysis (1980-2017).

The calculation of the slope failure initiation areas (starting points) is compiled through the combination of the initial landslide inventories and the estimated starting zones as determined by the high susceptible zones refined with the concave surface areas and the Topographic Wetness Index (TWI). The runout distance modelling is performed based on a rainfall-triggered scenario, with the combination of the multiple flow direction algorithm of Random Walk, enriched with a Monte-Carlo simulation procedure (Gamma, 2000), and the empirical-based approach of Angle of Reach (Hunter & Fell, 2003). For modelling the future prone affected areas, we use a hydrologically sound DEM, the calculated starting points, and the estimated friction angle values per point. The estimation of the friction angle is based on the fact that it tends toward lower angles with the increase of the catchment area (Wichmann, 2017). The validation of the aforementioned approach is compared with the calculated friction angles of the landslide inventory areas, using the Scheidegger (1973) theory. 

Our analysis results indicate that the largest percentage of the recorded landslide events are classified by the WoE method more efficiently, especially in medium-to-very risk classes. The estimated friction angle has less than one degree RMSE, which is highly accurate. Additionally, the runout distance paths and the risk susceptibility index are in a good agreement, as the spatial distribution of the runout is mainly located in very highly landslide susceptible areas. 

Our proposed method proves that the contribution of the geomorphological and climatological factors, enriched with GIS and EO approaches is a valuable tool for landslide susceptibility monitoring of CNH sites. The final products can be directly used to assist decision makers and stakeholders for anticipating risk mitigation measures.