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Methodology and Results

Landslides pose a recurrent natural hazard in almost all mountainous regions of the Earth, claiming people’s lives and destroying man-made infrastructures like buildings, roads, railways or mountain trails. Therefore, infrastructure maintainers, regional authorities and emergency services require information on past and new occurrences of landslides in order to protect infrastructure at risk and to manage the damages.

Practitioners require the location, extent and distribution of triggered landslides for analysis in conjunction with infrastructure information. Any relevant data source must be available in a timely manner for rapid mapping, documentation or monitoring of landslides. The derived information is valuable for the organization’s decision makers in their processes of managing landslide occurrences, damages and risk.

Landslide information is often collected by a combination of ground surveying and image interpretation following landslide triggering events. However, the high workload, limited availability of experts and narrow time window for information collection result in a necessary trade-off between completeness, accuracy and detail. This reduces the reliability and accuracy of the resulting landslide information. The increased amount of EO data at high spatial and temporal resolutions promotes the development of semi- automated landslide mapping approaches that enable the delivery of consistent results while reducing time and cost efforts.

The pre-operational service relies on a database of high resolution and very high resolution optical EO data from various sensors. Semi-automated mapping routines that are adaptable to changing EO data and geographical settings enable the identification of landslides. A web service provides access to EO data and integrates the mapping routines via a web processing chain. The user is able to map landslides and identify landslide-affected infrastructure.


The service concept and methodology will be developed and tested for several landslide affected study areas in Austria and northern Italy. Landslide maps and landslide change maps will be produced. The cooperating stakeholders and decision makers will gain access to the web service in order to explore the results and test the implemented mapping routines. The feedback will allow the quality of the pre-operational service, which aims at fast and straightforward information provision for targeted management of natural hazards, to be judged.