EO-based landslide mapping
EO-based landslide mapping: from methodological developments to automated web-based information delivery
Rainfall-triggered landslides in the Bregenzerwald, federal state of Vorarlberg, Austria.
© Geologische Bundesanstalt
Landslides are recurrent natural hazards in mountainous regions of the Earth, claimingpeople’s lives and destroying man-made infrastructures. Society and policy makers areinterested in knowing the location and spatial extent of landslides immediately after atriggering event, as well as in predicting landslides. Detailed, accurate and completelandslide maps are essential to meet these interests. Promoted by the increased availabilityand quality of Earth Observation (EO) data, attempts to automate the production of landslidemaps have recently been undertaken. As demonstrated by several case studies, especiallyobject-based image analysis (OBIA) provides methodologies that are valuable for automatedlandslide mapping. However, existing OBIA mapping routines have been targeted to specificdata sets and study areas, and can therefore be hardly transferred to other data sets orgeographical settings. In order to achieve a high degree of automation, objectivity, andgeneral applicability of an object-based landslide mapping system, the proposed project aimsat the following developments:
- Automated knowledge-based and statistical OBIA routines that are optimised forapplication to VHR (very high resolution) and HR (high resolution) optical EO data setsfor the polygon-based extraction of landslides after a triggering event;
- OBIA mapping routines that are automated and at the same time robust and flexible tochanging input optical EO data sets (and thus spatial resolution), as well geographical setting;
- Automated knowledge-based and statistical OBIA routines that are optimised forapplication to multi-temporal VHR and HR optical EO data sets for the polygon-baseddetection of landslide changes;
- An innovative and efficient web processing chain which comprises robust OBIAmapping routines for feeding a pre-operational service that allows for automatedpolygon-based landslide mapping based on VHR and HR optical EO data, as well asthe identification of landslide-affected infrastructure.
|Projektkurztitel||EO-based landslide mapping|
|Projektleitung||Interfaculty Department of Geoinformatics - Z_GIS, University of Salzburg|
|Projektmitglieder||GRID-IT - Gesellschaft für angewandte Geoinformatik mbH, Austria, Geologische Bundesanstalt (GBA), FA Ingenieurgeologie, Austria|
|Zeitraum||01.03.15 - 31.08.17|