Validation of landslide hazard models using a semantic engine on online news |
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| Institution: | 1. Department of Land, Environment, Agriculture and Forestry, University of Padova, Legnaro, Italy;2. Institute of Earth Sciences, Hebrew University of Jerusalem, Israel;3. Civil and Environmental Engineering, University of Connecticut, Storrs, CT, USA;4. Université de Grenoble/CNRS, Laboratoire d''étude des Transferts en Hydrologie et Environnement, LTHE, UMR 5564, Grenoble F-38041, France;1. Division of Geotechnical Engineering and Geosciences, Department of Civil and Environmental Engineering, UPC BarcelonaTECH, Jordi Girona 1-3, 08034 Barcelona, Spain;2. Key Laboratory of Western China''s Environmental Systems (Ministry of Education), College of Earth and Environmental Sciences, Lanzhou University, 222 South Tianshui Road, Lanzhou 730000, China;3. CREAF, Campus Universitat Autonoma Barcelona, Edifici C, 08193 Bellaterra (Cerdanyola del Vallès), Catalonia, Spain;4. Department of Geotechnical and Geological Hazard Prevention, Cartographic and Geological Institute of Catalonia, Parc de Montjuïc S/N, 08038 Barcelona, Spain |
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| Abstract: | The objective of this work is twofold: (i) automatically setting up a landslide inventory using a state-of-the art semantic engine based on data mining on online news and (ii) evaluating if the automatically generated inventory can be used to validate a regional scale landslide warning system based on rainfall-thresholds.The semantic engine scanned internet news in real time in a 50 months test period. At the end of the process, an inventory of approximately 900 landslides was automatically set up for the Tuscany region (23,000 km2, Italy). Using a completely automated procedure, the inventory was compared with the outputs of the regional landslide early warning system and a good correspondence was found, e.g. 84% of the events reported in the news is correctly identified by the warning system.On the basis of the obtained results, we conclude that automatic validation of landslide models using geolocalized landslide events feedback is possible. The source of data for validation can be obtained directly from the Internet channel using an appropriate semantic engine dedicated to perform a monitoring of the Google News aggregator.Moreover, validation statistics can be used to evaluate the effectiveness of the predictive model and, if deemed necessary, an update of the rainfall thresholds could be performed to obtain an improvement of the forecasting effectiveness of the warning system.In the near future, the proposed procedure could operate in continuous time and could allow for a periodic update of landslide hazard models and landslide early warning systems with minimum or none human intervention. |
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| Keywords: | Warning systems Automatic validation Semantic engine Geohazards Inventories Landslides Geotagging |
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