Abstract
or many years, statistical based landslide susceptibility maps have been used to spatially display the relative landslide probability of large areas. Consequently, such maps serve as guidance for strategic territorial planning. In Lower Austria (approx. 19200 km²) a complete set of landslide susceptibility maps for all municipalities has been implemented in 2014. These maps resulted from using 12889 slides as observations and fitting a generalized additive model (GAM) with a variety of geomorphically meaningful explanatory variables. Aiming at easy interpretable maps, the three susceptibility classes minor (78% of all pixels within Lower Austria), moderate (16%) and major (6%) were defined. In these classes, 5%, 25% and 70% of the landslides were in the categories 1, 2 and 3, respectively. Since the completion of these susceptibility maps, nearly eight years have passed, and many new landslides have been mapped. This study investigates, if and to which degree the existing landslide susceptibility maps can correctly predict these new events.
This research aims to quantify the accuracy of the spatial predictions. Recently mapped landslides were obtained from two different sources: damage reports related to the “Baugrundkataster", and landslides mapped from hillshades of a high-resolution LiDAR DTM. Additionally, information on the quality of the original landslide inventory and the new ones is used to analyze the effects of only using high quality inventories in this explorative comparison.
First results give a similar occurrence percentage of recently mapped landslides in the same classes, in comparison with the original classification design. Depending on the inventory the occurrence percentage varies especially in the 3rd class. Preliminary analysis indicates that, depending on the inventory, 34 to 63% of the new landslides are situated in the 3rd category (designed to contain 70%). However, it is also observed even for the lower quality inventories, that more than 90% of the landslides are not more than 30 meters away from merged 2nd and 3rd category susceptibility class. Depending on the new inventory, this percentage can reach 97%, while up to 94% of the points are at 0m distance of the 2nd and 3rd classes. This is of major importance for the application of these maps, e.g. within spatial planning. Additionally other preliminary analyses already indicate a better proportional correspondence of landslides coinciding with the most landslide-prone 3rd category, when excluding lower quality samples.
The landslide susceptibility map will be recalculated based on the newly recorded events. The potential change of the spatial prediction will be quantified, and the causes of these potential changes will be analyzed. The identical methodological design is applied to ensure comparability and quality control.